DESC:RELATED APPLICATION
Benefit is claimed to Indian Provisional Application No. 727/MUM/2015 titled "A SYSTEM AND METHOD FOR AMBIENT LIGHT DETECTION” filed on 5th March, 2015, which is herein incorporated in its entirety by reference for all purposes.

FIELD OF INVENTION
The field of invention generally relates to ambient light detection and more specifically relates to ambient light detection for a vehicle.

BACKGROUND OF INVENTION

Existing vehicles use a number of sensors for various functionalities such as for detecting ambient light, position, distance, speed, etc. Multiple sensors add to the overall cost of a system for detecting ambient light, apart from increasing the complexity and architecture of the solution.

Ambient light sensing is required in a variety of applications where the environment light has to be sensed. For example, for an automotive application, in high end vehicles, the ambient light sensors are used to adjust the backlight intensity of the instrument cluster or the LCD backlight of GPS devices or DVD screen. Also, ambient light needs to be detected in various scenarios, for example, when a vehicle enters a tunnel, under bridge/ canopy of trees, etc. Additionally, the ambient light sensing is required to automatically adjust camera mode from day to night, based on the ambient light sensed.

For ambient light detection, existing systems utilize optical/photo sensors that are typically used for light detection, like photodiode or phototransistors. The existing methods for tunnel detection typically use two ambient sensors. The first sensor has a wide field of view while other sensor has a narrow field of view. It senses ambient light conditions ahead of vehicle. The sensor reacts quickly to the sudden change in light. The combination of the two sensors detects the amount of light levels in the environment and automatically activates/deactivates the vehicles head lamps.

Currently, ambient light sensors exist in high end vehicle models. These sensors are basically optical sensors, generally, mounted on the windscreen inside the vehicle. The sensor tracks the various light levels in the environment and automatically activates/deactivates the vehicles head lamps.

However, the existing systems require a large number of sensors to detect the ambient light. This increases the cost and the system complexity. Thus, there is a need to reduce the number of sensors required to detect the ambient light and provide a cost effective and simple solution.

SUMMARY
The various embodiments of the present invention disclose a method and system for detecting ambient light. The method comprises capturing one or more visible images, converting the captured image into a grey color image, determining histogram of each of the grey color image, computing an average frequency mean value (FM) and a data mean value (DM) of the determined histogram, and performing one of a (a) comparing the FM with a predetermined FM threshold, and detecting the ambient light being an optimum light when the compared FM is greater than the predetermined FM threshold, (b) comparing the FM with a predetermined FM threshold and comparing the DM with the predetermined DM threshold, and detecting the ambient light being an optimum light when the compared FM is lesser than the predetermined FM threshold and the compared DM is greater than the predetermined DM threshold, and (c) comparing the FM with a predetermined FM threshold and comparing the DM with a predetermined DM threshold, and if the FM is lesser than the predetermined FM threshold and the DM is lesser than the predetermined DM threshold, comparing FM of an identified region of interest (ROI) with a predetermined FM threshold, and detecting the ambient light being less than the optimum light when the compared FM of the ROI is lesser than the predetermined FM threshold.

According to an embodiment herein, the method further comprises determining FM of the identified region of interest (ROI): identifying the region of interest in the captured image, and determining an FM of the identified region of interest (ROI) when the FM is less than the predetermined FM threshold, and the DM is less than the predetermined DM threshold.

According to an embodiment herein, computing the FM of the determined histogram, comprises: determining a frequency mean value of the determined histogram, for a predefined number of frames, and determining the FM for the predefined number of frames.

According to an embodiment herein, the method further comprises detecting a day time, when the detected ambient light is greater than the optimum light. Also, detecting a possible entry in and exit out from a tunnel, when the detected ambient light is less than the optimum light.

According to an embodiment herein, the method further comprising performing predefined control function based on detecting one or more states of the ambient light.

According to another embodiment of the present invention, a system for detecting ambient light, comprising: an image capturing device adapted to capture one or more images, and a processing unit connected to the image capturing device configured to perform the steps comprising: converting color of each of the captured image into a grey color, determining histogram of each of the grey color captured image, computing average frequency mean value (FM) and data mean value (DM) of the determined histogram, and performing one of a (a) comparing the FM with a predetermined FM threshold, and detecting the ambient light being an optimum light when the compared FM is greater than the predetermined FM threshold, (b) comparing the FM with a predetermined FM threshold, comparing the DM with the predetermined DM threshold, and detecting the ambient light being an optimum light when the compared FM is lesser than the predetermined FM threshold and the compared DM is greater than the predetermined DM threshold, and (c) comparing the FM with a predetermined FM threshold, comparing the DM with a predetermined DM threshold, and when the compared FM is less than the predetermined FM threshold and the DM is less than the predetermined DM threshold, comparing FM of an identified region of interest (ROI) with a predetermined FM threshold, and detecting the ambient light being less than the optimum light when the compared FM of the ROI is less than the predetermined FM threshold.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS

The aforementioned aspects and other features of the present invention will be explained in the following description, taken in conjunction with the accompanying drawings, wherein:

Figure 1 illustrates a block diagram of a system for detecting ambient light, according to an embodiment of the present invention.

Figure 2 is a schematic diagram illustrating an input image and a corresponding histogram, according to an embodiment of the present invention.

Figure 3 is a flow diagram illustrating a method of detecting ambient light conditions, according to an embodiment of the present invention.

Figure 4 is a schematic diagram illustrating different ambient light conditions and corresponding histograms, according to an embodiment of the present invention.

Figures 5a & 5b are schematic diagrams illustrating day time conditions with a low contrast image and a good contrast image, according to an embodiment of the present invention.

Figures 6a & 6b are schematic diagrams illustrating day time conditions where the average frequency mean value (FM) is less but data mean value (DM) is high, according to an embodiment of the present invention.

Figures 7a & 7b are schematic diagrams illustrating possible tunnel conditions, according to an embodiment of the present invention.

Figure 8a is a schematic diagram illustrating an entering tunnel, according to an embodiment of the present invention.

Figure 8b is a schematic diagram illustrating an in tunnel condition, according to an embodiment of the present invention.

Figure 9a is a schematic diagram illustrating an exiting tunnel condition, according to an embodiment of the present invention.

Figure 9b is a schematic diagram illustrating a final exit tunnel condition, according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The embodiments of the present invention will now be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiments. The present invention can be modified in various forms. Thus, the embodiments of the present invention are only provided to explain more clearly the present invention to the ordinarily skilled in the art of the present invention. In the accompanying drawings, like reference numerals are used to indicate like components.

The specification may refer to “an”, “one” or “some” embodiment(s) in several locations. This does not necessarily imply that each such reference is to the same embodiment(s), or that the feature only applies to a single embodiment. Single features of different embodiments may also be combined to provide other embodiments.

As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless expressly stated otherwise. It will be further understood that the terms “includes”, “comprises”, “including” and/or “comprising” when used in this specification, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations and arrangements of one or more of the associated listed items.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. In one embodiment, average frequency mean value is referred interchangeably as FM and FMavg.

The present invention describes method and system for detecting varying ambient light conditions in an environment.

Figure 1 illustrates a block diagram of a system for detecting ambient light, according to an embodiment of the present invention. The system comprises an image capturing device 101, a processing unit 102, and a display unit 103. The image capturing device 101 is adapted to capture one or more images. The processing unit 102 is connected to the image capturing device 101 to process the captured image. The processing unit 102 is adapted to perform the steps comprising converting color of each of the captured image into a grey color, determining histogram of each of the converted grey color image, computing data mean value (DM) and average frequency mean value (FM) of the determined histogram, comparing the average frequency mean value with a predetermined FM threshold for detecting ambient light. Additionally, the processing unit 102 compares the data mean value with a predetermined DM threshold when the average frequency mean value is less than the predetermined FM threshold for detecting ambient light. On detection of the ambient light to be less than optimal light, the system sends alert to user. In one embodiment, the visual alert is displayed on the display unit 103.

In one embodiment, the method and system is used for detecting ambient light using an on-board forward facing image capturing device 101 such as a camera 101 in a vehicle. The forward facing camera in the vehicle may be an existing camera of the driver assistance system or maybe retrofitted.

In this embodiment, the method of the present invention detects the ambient light in various road scene conditions which includes, but not limited to:
• Normal day light
• Entry/Exit into a tunnel
• Inside a tunnel/ entering parking/ garage/ closed area etc.
• Under bridge/ shadows due to canopy of trees etc.

When a vehicle is on the move, the forward facing camera 101 in the vehicle captures an image of the surrounding that is ahead of the vehicle. The captured image is then processed by the processing unit 102, where the ambient light and road scene conditions are detected by the control logic of the processing unit. Once the ambient light is detected to be less than optimal light, then the processing unit sends an alert to a user. In one embodiment, the alert is in the form of a message which is displayed on the display unit 103. In another embodiment, the electronic control unit 104 (ECU) performs a predefined control function based on the detected ambient light. The processing unit sends a signal to a light electronic control unit 104 (ECU) which in turn controls the one or more vehicle’s functionalities such as head lamp 105. The predefined control functions, include but not limited to, adjusting headlamps, dashboard lights, steering light automatically according to the road condition.

Figure 2 is a schematic diagram illustrating an input image and a corresponding histogram, according to an embodiment of the present invention. The image captured by the forward facing camera 101 of the vehicle is a color image as shown in Figure 2(a) and the processing unit 102 converts the captured color image into a grey image and subsequently the histogram of the image is determined as shown in Figure 2(b).

Figure 3 is a flow diagram illustrating a method of detecting ambient light conditions, according to an embodiment of the present invention. At step 301, the color image of the surrounding that is ahead of the vehicle is captured by the forward facing camera 101. At step 302, the captured color image is processed and converted by the processing unit 102 to the grey image. At step 303, the histogram of the processed image is determined. At step 304, from the determined histogram of the image, mean of the data which provides the average brightness of the image (Data Mean/ DM) and mean of the frequency values of the histogram are computed. At step 305, the computed FM is compared with the predetermined FM threshold. At step 306, the computed DM is compared with the predetermined DM threshold if the FM is less than the predetermined FM threshold. At step 307, based on the comparison, ambient lighting conditions are identified using which the flags and threshold values are defined. At step 308, appropriate alert/warnings are given/ displayed based on changing values of DM and FM with respect to the pre-defined threshold values.

According to an embodiment of the present invention, consider that the system for detecting ambient light is currently being booted during day time/sufficient ambient light. The average frequency mean value (FM) is computed for the present scene and the computed FM is compared with the predetermined FM threshold. If the FM is greater than the predetermined FM threshold, the scene is identified to be as day time and the ambient light is detected as optimal light. If the FM is lesser than the predetermined FM threshold, the data mean value (DM) is computed for the present scene and if the DM is greater than the predetermined DM threshold, the scene is identified as day time and the ambient light is detected as optimal light. Further, if the FM is lesser than the predetermined FM threshold and the DM is lesser than the predetermined DM threshold, a small area (region of interest) in the center of the image is selected and then the FM for the selected ROI is computed. The ambient light is detected as being less than the optimum light when the compared FM of the ROI is lesser than the predetermined FM threshold.

According to another embodiment of the present invention, consider that the system for detecting ambient light is currently being booted during night time/in a darker region/in a lesser ambient light region. The average frequency mean value (FM) and the data mean value (DM) are computed for the present scene. The FM and DM are compared with the predetermined threshold values. If the FM is greater than the predetermined FM threshold and the DM is greater than the predetermined DM threshold, the scene is identified as day time and the ambient light is detected as optimal light. If the FM is lesser than the predetermined FM threshold and the DM is greater than the predetermined DM threshold, the scene is identified as day time and the ambient light is detected as optimal light. Further, if the FM is lesser than the predetermined FM threshold and the DM is lesser than the predetermined DM threshold, a small area (region of interest) in the center of the image is selected and then the FM for the selected ROI is computed. The ambient light is detected as being less than the optimum light when the compared FM of the ROI is lesser than the predetermined FM threshold.

The “optimal light” referred to herein, includes but not limited to, light above a predefined threshold, bright light condition and a day time condition. The “less than optimal light” referred to herein, includes but not limited to light below a predefined threshold, low light condition, night time condition, tunnel, parking, garage, under bridge, canopy of trees, etc. When a less than optimal light condition is detected, the system displays an appropriate warning to the driver and the ECU controls the appropriate vehicle functionality.

For example, in one of the embodiments, the method of the invention detects a possible tunnel condition - entering tunnel, in-tunnel and exiting tunnel. The method for detection of possible tunnel is described in detail in the further description. If the FM of the selected ROI of the image is less than the predetermined FM threshold, the system warns that the region ahead is a possible tunnel and a warning message (‘Possible Tunnel’) is issued on the vehicle display. If this condition persists for a certain number of frames ‘n’, warning message would change to ‘Entering Tunnel’ for, for example, 10 frames and the “In_Tunnel” flag will be set. Once the “In_Tunnel” flag is set, it is assumed that the vehicle is in the tunnel area and ‘Inside Tunnel’ warning message is displayed. The FM is monitored for the in-tunnel situation and if it falls much below the predetermined FM threshold, the system warns that it might be an exit tunnel condition. Accordingly “Exiting tunnel” warning message will be provided and the “Exit_Tunnel” flag will be set. The ‘Exit Tunnel’ warning is displayed for, for example, about 15 frames. A final exit is monitored after the 15 frames of exit condition, until the FM becomes greater than the predetermined FM threshold. Once the FM becomes greater than the predetermined FM threshold, it indicates an optimal light and a day time condition and all the flags are reset accordingly.

According to an embodiment of the present invention, the algorithm used to identify a possible scenario includes the following steps:
a. Histogram Computation ( Total bins =256)
i. Computing the bin values of histogram
ii. Computing max value of the 256 bins
iii. Scaling the bin values with the max value

b. Frequency Mean and Data Mean
i. Computing average of the scaled bin values (Frequency mean)
ii. Computing data mean from bin values (Data Mean)

c. Road Scene Identification – Setting Threshold Values
i. Computing average of frequency mean over past 5 frames (FM)
ii. Setting threshold values for FM and DM (FM_THR, DM_THR, EXIT_THR)

d. Road Scene Identification – Method
i. Day time
1. If FM > FM_THR
2. Else if FM < FM_THR but DM > DM_THR
3. Else if FM < FM_THR && DM < DM_THR but FM_ROI > FM_THR
a. Counter 1= Counter 1-1;

ii. Possible Tunnel
1. If FM < FM_THR, DM < DM_THR && FM_ROI < FM_THR
2. Counter 1 = Counter1+1;

iii. Entering tunnel
1. If Counter 1>5, in_tunnel_flag =0
2. Counter 2 =Counter 2+1;
3. Repeat display ‘Entering tunnel’ until Counter 2 =10
4. In_tunnel_flag =1

iv. In_tunnel
1. If Counter 2 > 10 && In_tunnel_flag =1 && FM > FM_THR

v. Exit
1. If in_tunnel_flag =1, Counter 2>10 but FM < EXIT_THR
2. Exit_flag=1
3. Counter 3 = Counter 3 + 1

vi. Final Exit
1. If Counter 3==15
2. If FM < EXIT_THR, display ‘exit’ label
3. Else if FM > FM_THR, display ‘ day time’ label

The steps to detect the ambient light i.e., day time, possible tunnel, entering tunnel, in tunnel, exiting tunnel and final exit are explained in detail as follows:

a. Histogram Computation
For a given grey level image , of size with intensity (n) ranging from the histogram is computed as follows:

Step 1: Compute histogram bin values
Let ‘p’ denote the histogram bin of the image and ‘i’ denote the bin index
Then,
pi = Total number of pixels with intensity ni
Where, Eq. 1

Step 2: Compute maximum frequency value
Compute the maximum value of the computed histogram bin values. This value provides the maximum frequency value.
Max_p = max (pi) ( Eq. 2

Step 3: Scale the bin data with the maximum frequency value
= Eq. 3

Scaling the bin data with the maximum frequency value provides different frequency mean value for every histogram, thus providing information about the distribution. The details are explained in the following section.

b. Frequency Mean & Data Mean
Histogram provides the distribution of frequency or the distribution of brightness values.

Figure 4 is a schematic diagram illustrating different ambient light conditions and corresponding histograms, according to an embodiment of the present invention. The distribution of frequency for various road conditions such as day time, entering tunnel, in tunnel, exiting tunnel and final exit (outside tunnel) is disclosed. The histograms are generated for different ambient light conditions and that are different for each road condition. In case of non-normalized histogram, for example, the sum of the frequencies of the histogram bin is equal to the size of the image and in case of normalized histogram, it is equal to 1.

To obtain a singular value that could provide information about the distribution of frequency, the maximum frequency value of the distribution of frequency is computed, and the histogram value is scaled.
. Eq. 4

The frequency mean value from the scaled bin value is computed as follows
Eq. 5
Where,

Since for the entering tunnel or exiting tunnel condition, histogram would peak either close to zero or to 255 respectively, the maximum frequency value would remain similar and the frequency mean value would also be in the same range. To avoid erroneous decision, as the frequency mean value would also be in the same range, data/brightness mean value of the image is also compared.

The data mean or the brightness value of the image is computed from the histogram. The histogram value obtained in Eq. 1 is normalized as follows:
Eq. 6

The range of pi lies between 0 and 1
Eq. 7

c. Scene Identification: Setting Threshold Values
It is assumed that the system would turn on during the day time condition to identify the ambient light condition. Exemplary range of frequency mean and data mean values for various ambient light conditions are described below:

Table 1: Analysis results of 2 videos to compute thresholds for frequency mean and data mean values.

As shown in Table 1, the range of brightness value during a day time varies between 90 and 150, while the FM lies above 30. To clearly distinguish between day time and low ambient light scenarios, the predetermined DM threshold is set at 80 (DM_THR). It is observed that there exist fluctuations in the frequency mean value especially when the vehicle passes under bridges or canopy of trees. To avoid erroneous detections, average value of the frequency mean is computed. The average of the previous few frames are stored and estimated for the current frame. The FM is updated as follows:

Initially the frequency mean values of the first K frames are stored in an array, then for the current frame, the average of the previous K frames are computed as follows:

E.q 8

(FM of current image)
The threshold set for the FM is 30 (FM_THR). As shown in Table 1, during the exit condition, there is a sudden drop in the value of frequency mean. In order to distinguish between the exit condition and day time condition, the exit threshold for the FM is set at 20 (EXIT_THR).
FM_THR 30
DM_THR 80
EXIT_THR 20

Table 2: Thresholds defined for the system

d. Method to distinguish road scenes
Following ambient light conditions/ scenes are identified using this system: day time, possible tunnel, entering tunnel, in tunnel, exiting tunnel and final exit.

Figures 5a & 5b are schematic diagrams illustrating day time conditions with a low contrast image and a good contrast image, according to an embodiment of the present invention. As shown in Figure 5a, for example, the FM value is 54.2 and the DM value is 101.2 and both the FM and DM are above their threshold values 30 and 80 respectively. And similarly in Figure 5b, the FM value is 48.7 and the DM value is 128.05, where both the values are above their threshold values 30 and 80 respectively. Hence, if the FM is greater than the predetermined FM threshold (FM_THR), then the current frame is labelled as ‘Day Time’. The average of the previous frames is taken, hence if there is a sudden reduction in ambient light, erroneous determination of the road condition could be avoided.

Figures 6a & 6b are schematic diagrams illustrating day time conditions where the average frequency mean value (FM) is less but data mean value (DM) is high, according to an embodiment of the present invention. As shown in Figure 6b, the FM value is 7.28 and the DM value is 87.5. Here, the FM is less than the predetermined FM threshold (FM_THR) 30 but the DM of the current image is greater than the predetermined DM threshold (DM_THR) 80, hence the current frame is labelled as ‘Day Time’.

Further, as shown in Figure 6a, the FM value is 29.02 and the DM value is 68.64. Here both the FM and the DM are less than their respective threshold values 30 and 80, therefore a region of interest (ROI) in the image center of fixed width and height is extracted. The FM of the current ROI is compared with the predetermined FM threshold (FM_THR) and if found greater, then the current frame is labelled as ‘Day Time’.

Figures 7a & 7b are schematic diagrams illustrating possible tunnel conditions, according to an embodiment of the present invention. If in the above last case as described in Figure 6, the FM of the current ROI is less than the predetermined FM threshold (FM_THR), then the current frame is labelled as ‘Possible Tunnel’. This condition is monitored by incrementing counter value (counter_1) until five frames.

Figures 8a & 8b are schematic diagrams illustrating an entering tunnel and an in tunnel condition, according to an embodiment of the present invention. If the counter value (counter_1) is more than five, the current frame label is switched to ‘Entering tunnel’ as shown in Figure 8a. The counter (counter_1) is decremented if the day time scenario is encountered. After five frames, the entering tunnel condition is maintained for next consecutive ten frames (counter_2), after which the ‘In Tunnel’ flag is set as shown in Figure 8b. Until the FM falls below the exit threshold value (EXIT_THR), the current frame is labelled as ‘In-tunnel’.

Figure 9a is a schematic diagram illustrating an exiting tunnel condition, according to an embodiment of the present invention. The exiting tunnel conditions are monitored only if the in tunnel flag is set. If the FM falls below the exit threshold value (EXIT_THR), then the current frame is labelled as ‘Exiting Tunnel’ and the exit counter (counter_3) is incremented. Also during exit it is observed that the brightness value increases drastically. This conditioned is also monitored to avoid erroneous detection of the exit condition. The exit condition is displayed for around 15 frames (counter_3). After this the exit tunnel flag is set and the final exit condition is monitored.

Figure 9b is a schematic diagram illustrating a final exit tunnel condition, according to an embodiment of the present invention. If the FM is less than the exit threshold value (EXIT_THR), the current frame is labelled as ‘Exiting Tunnel’ else, the current frame is labelled as ‘Day Time’. The flags and counters are reset to detect further tunnel like conditions.

The three counters are set so that the switching over from one scene to other is not abrupt. The first counter (counter_1) monitors the possible tunnel condition for 5 frames. The counter_1 decrements if the ‘Day Time’ condition is encountered. The second counter (counter_2) monitors entering tunnel condition and retains the ‘Entering Tunnel’ condition for the next consecutive 10 frames. The third counter (counter_3) maintains the exit tunnel condition for around 15 frames.

Two additional flags (in_tunnel and exit flag) ensure that the switchover from the in_tunnel condition to the day time condition and from the exit condition to the day time condition does not happen in a random fashion. Once the entering tunnel is detected, the in_tunnel flag is set, this ensures that the next condition would be in tunnel until exit condition is reached. Only after the exit flag is set, the day time condition is monitored else it is labelled as exiting tunnel.

The method and system of the present invention is a simple and accurate ambient light detection system. The detection method of the present invention helps in distinguishing various low light conditions, like, but not limited to, tunnel like conditions, parking, under bridge, canopy of trees, etc. The present invention provides appropriate warnings such as ‘Possible tunnel’ and ‘Entering tunnel’, as appropriate. Further, the ECU performs a predefined control function based on the amount of ambient light detected. The ECU controls the one or more vehicle’s functionalities based on the ambient light detected. The predefined control function includes, but not limited to, adjusting headlamps, dashboard lights, steering light automatically according to the road condition. As described in the present invention, the entire classification of road scene conditions and the detection of ambient light is achieved by using only two parameters which are the average frequency mean value (FM) and the data mean value (DM).

All equivalent relationships to those illustrated in the drawings and described in the application are intended to be encompassed by the present invention. The examples used to illustrate the embodiments of the present invention, in no way limit the applicability of the present invention to them. It is to be noted that those with ordinary skill in the art will appreciate that various modifications and alternatives to the details could be developed in the light of the overall teachings of the disclosure, without departing from the scope of the invention.
,CLAIMS:
1. A method of detecting ambient light, comprising:
capturing one or more visible images;
converting the captured image into a grey color image;
determining histogram of each of the grey color image;
computing an average frequency mean value (FM) and a data mean value (DM) of the determined histogram; and
performing one of a
a) comparing the FM with a predetermined FM threshold; and
detecting the ambient light being an optimum light when the compared FM is greater than the predetermined FM threshold;
b) comparing the FM with a predetermined FM threshold and comparing the DM with the predetermined DM threshold; and
detecting the ambient light being an optimum light when the compared FM is lesser than the predetermined FM threshold and the compared DM is greater than the predetermined DM threshold; and
c) comparing the FM with a predetermined FM threshold and comparing the DM with a predetermined DM threshold; and
if the FM is lesser than the predetermined FM threshold and the DM is lesser than the predetermined DM threshold;
comparing FM of an identified region of interest (ROI) with a predetermined FM threshold; and
detecting the ambient light being less than the optimum light when the compared FM of the ROI is lesser than the predetermined FM threshold.

2. The method as claimed in claim 1 further comprising determining FM of the identified region of interest (ROI):
identifying the region of interest in the captured image; and
determining an FM of the identified region of interest (ROI) when the FM is less than the predetermined FM threshold, and the DM is less than the predetermined DM threshold.

3. The method as claimed in claim 1, wherein computing the FM of the determined histogram, comprises:
determining a frequency mean value of the determined histogram, for a predefined number of frames; and
determining the FM for the predefined number of frames.

4. The method as claimed in claim 1 further comprising detecting a day time, when the detected ambient light is greater than the optimum light.

5. The method as claimed in claim 1 further comprising detecting a possible entry in and exit out from a tunnel, when the detected ambient light is less than the optimum light.

6. The method as claimed in claim 1 further comprises of performing predefined control function based on detecting one or more states of the ambient light.

7. A system for detecting ambient light, comprising:
an image capturing device adapted to capture one or more images; and
a processing unit connected to the image capturing device configured to perform the steps comprising:
converting color of each of the captured image into a grey color;
determining histogram of each of the grey color captured image;

computing average frequency mean value (FM) and data mean value (DM) of the determined histogram; and
performing one of a
a) comparing the FM with a predetermined FM threshold; and
detecting the ambient light being an optimum light when the compared FM is greater than the predetermined FM threshold;

b) comparing the FM with a predetermined FM threshold;
comparing the DM with the predetermined DM threshold; and
detecting the ambient light being an optimum light when the compared FM is lesser than the predetermined FM threshold and the compared DM is greater than the predetermined DM threshold; and

c) comparing the FM with a predetermined FM threshold;
comparing the DM with a predetermined DM threshold;
when the compared FM is less than the predetermined FM threshold and the DM is less than the predetermined DM threshold;
comparing FM of an identified region of interest (ROI) with a predetermined FM threshold; and
detecting the ambient light being less than the optimum light when the compared FM of the ROI is less than the predetermined FM threshold.

8. The system as claimed in claim 7, wherein the processor is further configured to perform steps to determine FM of the identified region of interest (ROI):
identifying the region of interest in the captured image; and
determining an FM of the identified region of interest (ROI) when the FM is less than the predetermined FM threshold, and the DM is less than the predetermined DM threshold.