Description:
BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a traffic penalization system and particularly to a system for detection and reconstruction of obscured license plates with challan generation.
Description of Related Art
[002] In recent years, the use of automated systems for traffic enforcement has grown rapidly in urban environments. Authorities rely heavily on Automated Number Plate Recognition (ANPR) systems to identify vehicles, monitor traffic violations, and streamline the issuance of penalties. These systems capture images of license plates and extract the registration numbers for verification and record-keeping purposes. However, effective operation of such systems depends on clear visibility of license plates at all times, under various environmental and physical conditions.
[003] Despite the widespread deployment of ANPR technology, current systems face significant limitations in scenarios where vehicle number plates are obscured. Factors such as dirt accumulation, physical damage, deliberate covering, or structural design flaws often prevent accurate detection. Traffic cameras record the presence of a vehicle yet fail to provide meaningful identification when plate visibility remains compromised. In these instances, enforcement agencies must resort to manual intervention, that lacks efficiency, introduces subjectivity, and often leads to low violation resolution rates.
[004] Additionally, existing traffic enforcement systems focus primarily on detection of visible plates rather than restoration of unreadable or incomplete data. No known commercial solution incorporates advanced techniques to recover or infer missing plate details from obscured inputs. While intelligent traffic systems and machine learning tools support vehicle tracking or anomaly detection, they do not offer solutions for reconstructing critical vehicle identity data lost due to plate damage or concealment.
[005] There is thus a need for an improved and advanced system for detection and reconstruction of obscured license plates with challan generation that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide a system for challan generation. The system comprising a data acquisition unit adapted to receive images from an image capturing unit. The image capturing unit is adapted to capture the images of a license plate. The system further comprising a processing unit communicatively connected to the data acquisition unit. The processing unit is configured to receive the images from the data acquisition unit; extract characters in the received images using an Optical Character Recognition (OCR) algorithm; identify vehicle attributes using a computational algorithm; reconstruct missing characters in the characters extracted using the Optical Character Recognition (OCR) algorithm; match the reconstructed characters and the identified vehicle attributes with a database; generate a challan with a fine corresponding to an offence, when a match of the combination of the characters and vehicle attributes is matched in the database to identify an accurate owner of the vehicle; generate a challan with a fine corresponding to an offence upon matching the reconstructed characters and the identified vehicle attributes; and transmit a notification to a user device of the identified owner of the vehicle indicating an issuance of the challan.
[007] Embodiments in accordance with the present invention further provide a method for challan generation. The method comprising steps of receiving images of a license plate of a vehicle from an image capturing unit; extracting characters in the received images using an Optical Character Recognition (OCR) algorithm; identifying vehicle attributes using a computational algorithm; reconstructing missing characters in the characters extracted using the Optical Character Recognition (OCR) algorithm; matching the reconstructed characters and the identified vehicle attributes with a database; generating a challan with a fine corresponding to an offence, when a match of the combination of the characters and vehicle attributes is matched in the database to identify an accurate owner of the vehicle; generating a challan with a fine corresponding to an offence upon matching the reconstructed characters and the identified vehicle attributes; and transmitting a notification to a user device of the identified owner of the vehicle indicating an issuance of the challan.
[008] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide a system for detection and reconstruction of obscured license plates with challan generation.
[009] Next, embodiments of the present application may provide a system for challan generation that reconstructs missing or hidden number plate details using vehicle attributes such as color, make, and model, ensuring accurate identification even when the plate is partially or completely unreadable.
[0010] Next, embodiments of the present application may provide a system for challan generation that identifies the most probable vehicle match and issues challans automatically, eliminating the need for manual intervention.
[0011] Next, embodiments of the present application may provide a system for challan generation that strengthens road rule enforcement by ensuring that violators cannot evade detection through plate tampering, thus promoting higher compliance with traffic regulations.
[0012] Next, embodiments of the present application may provide a system for challan generation that standardizes the process, improving accuracy in detecting violations and issuing penalties.
[0013] Next, embodiments of the present application may provide a system for challan generation that supports large-scale implementation using existing camera infrastructure and low-cost AI models, making it suitable for nationwide use without major additional investments.
[0014] These and other advantages will be apparent from the present application of the embodiments described herein.
[0015] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0017] FIG. 1 illustrates a system for challan generation, according to an embodiment of the present invention;
[0018] FIG. 2 illustrates a block diagram of a processing unit, according to an embodiment of the present invention; and
[0019] FIG. 3 depicts a flowchart of a method for challan generation, according to an embodiment of the present invention.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates a system 100 for challan generation, according to an embodiment of the present invention. In an embodiment of the present invention, the system 100 may be adapted to read license plates installed on a vehicle. Further, if illegible, the system 100 may process the license plates. Moreover, if the corresponding may be offending and violating traffic rules, the system 100 may generate a challan with a fine corresponding to the offence. The system 100 may demotivate tampering with the license plates and may maintain regularization of traffic rules.
[0025] According to the embodiments of the present invention, the system 100 may incorporate non-limiting hardware components to enhance the processing speed and efficiency such as the system 100 may comprise an image capturing unit 102, a data acquisition unit 104, a processing unit 106, an Optical Character Recognition (OCR) algorithm 108, a computational algorithm 110, a database 112, and a user device 114. In an embodiment of the present invention, the hardware components of the system 100 may be integrated with computer-executable instructions for overcoming the challenges and the limitations of the existing systems.
[0026] In an embodiment of the present invention, the image capturing unit 102 may be adapted to capture the images of the license plate. The image capturing unit 102 may be installed on pathways such as, roads, freeways, highways, expressways, and so forth. The image capturing unit 102 may be installed at an angle optimum for capturing the images of the license plate installed on the vehicle. The image capturing unit 102 may further upload the captured images of the license plate to the system 100. The image capturing unit 102 may be, but not limited to, a camera, an infrared blaster, and so forth. In a preferred embodiment of the present invention, the image capturing unit 102 may be a traffic camera. Embodiments of the present invention are intended to include or otherwise cover any type of the image capturing unit 102, including known, related art, and/or later developed technologies.
[0027] In an embodiment of the present invention, the image acquisition unit 104 may be adapted to receive the images of the license plate from the image capturing unit 102.
[0028] In an embodiment of the present invention, the processing unit 106 may be in communication with the image acquisition unit 104. The processing unit 106 may further be configured to execute computer-executable instructions to generate an output relating to the system 100. According to embodiments of the present invention, the processing unit 106 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processing unit 106 including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processing unit 106 may further be explained in conjunction with FIG. 2.
[0029] FIG. 2 illustrates a block diagram of the processing unit 106, according to an embodiment of the present invention. The processing unit 106 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data processing module 202, a data comparison module 204, and a challan module 206.
[0030] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the images from the data acquisition unit 104. The data receiving module 200 may be configured to transmit the images to the data processing module 202.
[0031] The data processing module 202 may be activated upon receipt of the images from the data receiving module 200. In an embodiment of the present invention, the data processing module 202 may be configured to extract characters in the received images using the Optical Character Recognition (OCR) algorithm 108. Further, if the extracted characters may be missing characters or if the extracted characters may be illegible for the system 100 to read, then the data processing module 202 may reactivate the Optical Character Recognition (OCR) algorithm 108 to reconstruct missing characters in the characters extracted.
[0032] Further, upon recollection of the extracted characters, the data processing module 202 may deploy the computational algorithm 110 for identification of vehicle attributes. The vehicle attributes may be, but not limited to, a model of a vehicle, a make of the vehicle, a type of the vehicle, a tier of the vehicle, a color of the vehicle, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the vehicle attributes, including known, related art, and/or later developed technologies. The computational algorithm 110 may be, but not limited to, a machine learning model for vehicle recognition, an artificial intelligence algorithm, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the computational algorithm 110, including known, related art, and/or later developed technologies.
[0033] Upon extraction of the characters and identification of the vehicle attributes, the data processing module 202 may be configured to transmit the extracted characters and the vehicle attributes to the data comparison module 204.
[0034] The data comparison module 204 may be activated upon receipt of the extracted characters and the vehicle attributes from the data processing module 202. In an embodiment of the present invention, the data comparison module 204 may be configured to match the characters and the identified vehicle attributes. The matching may be conducted by running the characters in the database 112 to extract the vehicle attributes corresponding to the characters. Further, the extracted vehicle attributes may be compared with the identified vehicle attributes. The matching of the extracted vehicle attributes and the identified vehicle attributes may ensure characterization and correct identification of an accurate owner of the vehicle.
[0035] However, if the identified vehicle attributes may be unmatched with the extracted vehicle attributes, then the owner of the vehicle, corresponding to the identified number place may be impeached under a law enforcement body. Such scenarios may notate an interchange and/or an exchange of the license plate between and/or among vehicles. Further, if the owner and/or driver of the vehicle may be disobeying and/or breaking the traffic rules and creating traffic violations, then the data comparison module 204 may transmit a fine imposition signal to the challan module 206.
[0036] The challan module 206 may be activated upon receipt of the fine imposition signal from the data comparison module 204. In an embodiment of the present invention, the challan module 206 may be configured to generate the challan with the fine corresponding to the offence and/or the created traffic violation. Further, the challan module 206 may be configured to transmit a notification to the user device 114 of the identified owner of the vehicle indicating an issuance of the challan. The notification received on the user device 114 may be in a pre-defined form, in an embodiment of the present invention. The pre-defined form of the notification received on the user device 114 may be, but not limited to a pop-up notification, a flash notification, a ringer notification, a silent notification, a push notification, a hidden notification, an electronic mail notification, a Short Message Service (SMS) notification, an always on-screen notification, and so forth. Embodiments of the present invention are intended to include or otherwise cover any pre-defined form of the notification that may be received on the user device 114, including known, related art, and/or later developed technologies.
[0037] In an embodiment of the present invention, the user device 114 may be an electronic device used by an owner of the vehicle, a law enforcement, a transportation department, and so forth. The user device 114 may be adapted to receive the notification from the challan module 206. Further, the user device 114 may be adapted to receive the issued challan. The user device 114 may further be adapted to enable the owner of the vehicle to pay the fine corresponding to the generated challan. The user device 114 may be, but not limited to, a mobile phone, a smart phone, a laptop, a Point of Sale (POS) machine, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the user device 114, including known, related art, and/or later developed technologies.
[0038] FIG. 3 depicts a flowchart of a method 300 for detection and reconstruction of obscured license plates with challan generation, according to an embodiment of the present invention.
[0039] At step 302, the system 100 may receive the images from the image capturing unit 102.
[0040] At step 304, the system 100 may extract the characters in the received images using the Optical Character Recognition (OCR) algorithm 108.
[0041] At step 306, the system 100 may identify the vehicle attributes using the computational algorithm 110.
[0042] At step 308, the system 100 may reconstruct the missing characters in the characters extracted using the Optical Character Recognition (OCR) algorithm 108.
[0043] At step 310, the system 100 may match the reconstructed characters and the identified vehicle attributes with the database 112 to identify the accurate owner of the vehicle.
[0044] At step 312, the system 100 may generate the challan with the fine corresponding to the offence upon matching the reconstructed characters and the identified vehicle attributes.
[0045] At step 314, the system 100 may transmit the notification to the user device 114 of the identified owner of the vehicle indicating the issuance of the challan.
[0046] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0047] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. A system (100) for challan generation, the system (100) comprising:
a data acquisition unit (104) adapted to receive images from an image capturing unit (102), wherein the image capturing unit (102) is adapted to capture the images of a license plate of a vehicle; and
a processing unit (106) communicatively connected to the data acquisition unit (104), characterized in that the processing unit (106) is configured to:
receive the images from the data acquisition unit (104);
extract characters in the received images using an Optical Character Recognition (OCR) algorithm (108);
identify vehicle attributes of the vehicle using a computational algorithm (110);
reconstruct missing characters in the characters extracted using the Optical Character Recognition (OCR) algorithm (108);
match the reconstructed characters and the identified vehicle attributes with a database (112) to identify an accurate owner of the vehicle;
generate a challan with a fine corresponding to an offence upon matching the reconstructed characters and the identified vehicle attributes; and
transmit a notification to a user device (114) of the identified owner of the vehicle indicating an issuance of the challan.
2. The system (100) as claimed in claim 1, wherein the vehicle attributes are selected from a model of the vehicle, a make of the vehicle, a type of the vehicle, a tier of the vehicle, a color of the vehicle, or a combination thereof.
3. The system (100) as claimed in claim 1, wherein the user device (114) is an electronic device used by an owner of the vehicle, a law enforcement, a transportation department, or a combination thereof.
4. The system (100) as claimed in claim 1, wherein the user device (114) enables an owner of the vehicle to pay the fine corresponding to the generated challan.
5. The system (100) as claimed in claim 1, wherein the computational algorithm (110) is a machine learning model for vehicle recognition, an artificial intelligence algorithm, or a combination thereof.
6. The system (100) as claimed in claim 1, wherein the image capturing unit (102) is a traffic camera.
7. A method (300) for challan generation, the method (300) is characterized by steps of:
receiving images of a license plate of a vehicle from an image capturing unit (102);
extracting characters in the received images using an Optical Character Recognition (OCR) algorithm (108);
identifying vehicle attributes using a computational algorithm (110);
reconstructing missing characters in the characters extracted using the Optical Character Recognition (OCR) algorithm (108);
matching the reconstructed characters and the identified vehicle attributes with a database (112) to identify an accurate owner of the vehicle;
generating a challan with a fine corresponding to an offence upon matching the reconstructed characters and the identified vehicle attributes; and
transmitting a notification to a user device (114) of the identified owner of the vehicle indicating an issuance of the challan.
8. The method (300) as claimed in claim 7, wherein the vehicle attributes are selected from a model of the vehicle, a make of the vehicle, a type of the vehicle, a tier of the vehicle, a color of the vehicle, or a combination thereof.
9. The method (300) as claimed in claim 7, wherein the user device (114) is an electronic device used by an owner of the vehicle, a law enforcement, a transportation department, or a combination thereof.
10. The method (300) as claimed in claim 7, wherein the user device enables an owner of the vehicle to pay the fine corresponding to the generated challan.
Date: May 12, 2025
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant