SYSTEMS AND METHODS FOR CORRECTING GEOMETRIC DISTORTIONS IN VIDEOS AND IMAGES FIELD OF THE INVENTION: The invention relates generally to correct one or more geometric distortions, and in particular, to a system and method for correcting geometric distortions in video or image contents. BACKGROUND: The advancement in multimedia and networking technologies along with the availability of multitude of end user devices have enabled easy creation, sharing and distribution of multimedia content over the Internet at any time and from anywhere in the world. However, these advancements have raised security concerns. To tackle such challenges, digital watermarking has emerged as a promising solution. Digital watermarking techniques aim at embedding a message inside the digital content (images or videos) which can be extracted later on from the suspected files for proving the digital rights. However, the advancement in multimedia technologies have facilitated easy manipulation of the digital videos. Such manipulations can be intentional or unintentional and can obscure in watermark detection. These manipulations can be classified as simple image processing attacks such as compression or geometric attacks such as scaling. A number of image as well as video watermarking methods are available in literature which are robust against simple image processing attacks. However, majority of the techniques are vulnerable to geometric distortions. Geometric distortions in watermarked content lead to synchronization issues and ultimately result in loss of watermark. Present techniques to correct geometric distortions are non-blind in nature and application of such geometric correction methods is limited to digital images only. Additionally, these techniques are not applicable for videos due to its temporal nature and presence of different special effects such as fading and dissolve. SUMMURY: The present technique overcomes the above mentioned limitation by identifying the geometric distortion parameters and then correcting these identified geometric distortions. This technique is robust against any kind of geometric distortion in images as well as videos. According to the present embodiment, a method for correcting one or more geometric distortions in a video content and in an image is disclosed. In case of correcting the one or more geometric distortions in the video content, the method includes mapping a plurality of geometrically distorted frames with a plurality of original frames of the video content. After that, one or more features associated with the plurality of mapped geometrically distorted frames and original frames are identified, wherein the one or more features are insensitive to the one or more geometric distortions. Thereafter, the one or more features of the plurality of mapped geometrically distorted frames with original frames are mapped based on a predefined similarity threshold. Further, one or more geometric distortion parameters are determined from the one or more mapped features. Then, a frame level average distortion of each of the one or more geometric distortion parameters is determined. After that, a video level average distortion of each of the one or more geometric distortion parameters is determined based on the frame level average distortion. Finally, the one or more geometric distortions of the video content are corrected based on the video level average distortion of each of the one or more geometric distortion parameters. In case of correcting the one or more geometric distortions in the image, the method includes identifying one or more features associated with an original image and a geometrically distorted image, wherein the one or more features are insensitive to the one or more geometric distortions. Thereafter, the one or more features of the original image and geometrically distorted image are mapped based on a predefined similarity threshold. After that, one or more geometric distortion parameters are determined from the one or more mapped features. Then, an average distortion value of the one or more mapped features is determined with respect to the one or more geometric distortion parameters. Finally, the one or more geometric distortions are corrected based on the average distortion value of the one or more mapped features. In an additional embodiment, a system for correcting one or more geometric distortions in a video content and in an image is disclosed. In case of correcting the one or more geometric distortions in the video content, the system includes a frame mapping component, a feature identifier, a feature mapping component, a geometric distortion parameter determination component, a frame level average distortion determination component, a video level average distortion determination component and a geometric distortion corrector. The frame mapping component is configured to map a plurality of geometrically distorted frames with a plurality of original frames of the video content. The feature identifier is configured to identify one or more features associated with the plurality of mapped geometrically distorted frames and original frames, wherein the one or more features are insensitive to the one or more geometric distortions. The feature mapping component is configured to map the one or more features of the plurality of mapped geometrically distorted frames with original frames based on a predefined similarity threshold. The geometric distortion parameter determination component is configured to determine one or more geometric distortion parameters from the one or more mapped features. The frame level average distortion determination component is configured to determine a frame level average distortion of each of the one or more geometric distortion parameters. The video level average distortion determination component is coniigured to determine a video level average distortion 01 eacn oi tne one or more geometric distortion parameters based on the frame level average distortion. The geometric distortion corrector is coniigured to correct the one or more geometric distortions of the video content based on the video level average distortion of each of the one or more geometric distortion parameters. In case of correcting the one or more geometric distortions in the image, the system includes a feature identifier, a feature mapping component, a geometric distortion parameter determination component, an average distortion value determination component and a geometric distortion corrector. The feature identifier is configured to identify one or more features inside an original image and a geometrically distorted image, wherein the one or more features are insensitive to the one or more geometric distortions. The feature mapping component is configured to map the one or more features of the original image with the geometrically distorted image based on a predefined similarity threshold. The geometric distortion parameter determination component is configured to determine one or more geometric distortion parameters from the one or more mapped features. The average distortion value determination component is configured to determine an average distortion value of the one or more mapped features with respect to the one or more geometric distortion parameters. The geometric distortion corrector is configured to correct the one or more geometric distortions based on the average distortion value of the one or more mapped features. In another embodiment, a computer readable storage medium for correcting one or more geometric distortions in a video content and in an image is disclosed. In case of correcting the one or more geometric distortions in the video content, the computer readable storage medium which is not a signal stores computer executable instructions for mapping a plurality of geometrically distorted frames with a plurality of original frames of the video content, identifying one or more features associated with the plurality of mapped geometrically distorted frames and original frames, mapping the one or more features of the plurality of mapped geometrically distorted frames with original frames based on a predefined similarity threshold, determining one or more geometric distortion parameters from the one or more mapped features, determining a frame level average distortion of each of the one or more geometric distortion parameters, determining a video level average distortion of each of the one or more geometric distortion parameters based on the frame level average distortion and correcting the one or more geometric distortions of the video content based on the video level average distortion of each of the one or more geometric distortion parameters. In case of correcting the one or more geometric distortions in the image, the computer readable storage medium which is not a signal stores computer executable instructions for identifying one or more features associated with an original image and a geometrically distorted image, mapping the one or more features of the original image and geometrically distorted image based on a predefined similarity threshold, determining one or more geometric distortion parameters from the one or more mapped features, determining an average distortion value of the one or more mapped features with respect to the one or more geometric distortion parameters and correcting the one or more geometric distortions based on the average distortion value of the one or more mapped features. DRAWINGS: Various embodiments of the invention will, hereinafter, be described in conjunction with the appended drawings. There is no intention to limit the scope of the invention to such blocks or objects, or to any particular technology. Instead these simplified diagrams are presented by way of illustration to aid in the understanding of the logical functionality of one or more aspects of the instant disclosure and is not presented by way of limitation. FIG.l is a computer architecture diagram illustrating a computing system capable of implementing the embodiments presented herein. FIG. 2 is a flowchart, illustrating a method for correcting one or more geometric distortions in a video content, in accordance with an embodiment of the present invention. FIG. 3 depicts mapped features between the original frame and distorted frame, in accordance with an embodiment of the present invention. FIG. 4 depicts rotation angle between the corresponding features of the original frame and distorted frame, in accordance with an embodiment of the present invention. FIG. 5 illustrates computation of rotation angle between the corresponding feature of the original frame and distorted frame, in accordance with an embodiment of the present invention. FIG. 6 depicts horizontal and vertical distances between features within a frame, in accordance with an embodiment of the present invention. FIG. 7 is a flowchart, illustrating a method for correcting one or more geometric distortions in an image, in accordance with an embodiment of the present invention. FIG. 8 is a block diagram illustrating a system for correcting one or more geometric distortions in a video content, in accordance with an embodiment of the present invention. FIG. 9 is a block diagram illustrating a system for correcting one or more geometric distortions in an image, in accordance with an embodiment of the present invention. DETAILED DESCRIPTION: The foregoing has broadly outlined the features and technical advantages of the present disclosure in order that the detailed description of the disclosure that follows may be better understood. Additional features and advantages of the disclosure will be described hereinafter which form the subject of the claims of the disclosure. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the disclosure as set forth in the appended claims. The novel features which are believed to be characteristic of the disclosure, both as to its organization and method of operation, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present disclosure. Exemplary embodiments of the present invention provide a system and method for correcting one or more geometric distortions. To correct the one or more geometric distortions in videos, the frames of the original and distorted video are mapped at the beginning and then the features associated with the mapped frames which are insensitive to geometric distortions are identified. In case of correcting geometric distortions in images, frame mapping is not required and thus the process starts from identifying the features insensitive to geometric distortions in the original image and distorted image. Then, the geometric distortion parameters are identified from the mapped features. After that, an average distortion of the mapped features in a frame is determined with respect to all the geometric distortion parameters. In case of video, an average distortion of all the frames is calculated based on the average distortion of the features in each frame to correct the geometric distortion. FIG.l illustrates a generalized example of a suitable computing environment 100 in which all embodiments, techniques, and technologies of this invention may be implemented. The computing environment 100 is not intended to suggest any limitation as to scope of use or functionality of the technology, as the technology may be implemented in diverse general-purpose or special-purpose computing environments. For example, the disclosed technology may be implemented using a computing device (e.g., a server, desktop, laptop, hand-held device, mobile device, PDA, etc.) comprising a processing unit, memory, and storage storing computer-executable instructions implementing the service level management technologies described herein. The disclosed technology may also be implemented with other computer system configurations, including hand held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, a collection of client/server systems, and the like. With reference to FIG. 1, the computing environment 100 includes at least one central processing unit 102 and memory 104. The central processing unit 102 executes computer-executable instructions. In a multi-processing system, multiple processing units execute computer-executable instructions to increase processing power and as such, multiple processors can be running simultaneously. The memory 104 may be volatile memory (e.g., registers, cache, RAM), non-volatile memory (e.g., ROM, EEPROM, flash memory, etc.), or some combination of the two. The memory 104 stores software 116 that can implement the technologies described herein. A computing environment may have additional features. For example, the computing environment 100 includes storage 108, one or more input devices 110, one or more output devices 112, and one or more communication connections 114. An interconnection mechanism (not shown) such as a bus, a controller, or a network, interconnects the components of the computing environment 100. Typically, operating system software (not shown) provides an operating environment for other software executing in the computing environment 100, and coordinates activities of the components of the computing environment 100. FIG. 2 is a flowchart, illustrating a method for correcting one or more geometric distortions in a video content, in accordance with an embodiment of the present invention. Geometrically distorted frames are mapped with the original frames, as in step 202. The video consists of several frames and it is difficult to compare each frame of distorted video with each frame of original video manually. To address this problem, other well known properties of videos can be utilized. One of such property is a scene. Scene is a continuous sequence of frames which represents a continuous action captured by a camera. Any presently known scene detection algorithm can be used for detecting the scenes in the original and distorted video and one of such algorithms is mentioned in Indian Patent Application number 4233/CHE/2013. To map the original and geometrically distorted scenes, an average image per scene is calculated. The average image is the average of corresponding pixels of all the frames in the scene. The average images in the original and distorted videos can be represented as where Iavg and l'avg represent the average image per scene in original and distorted videos respectively, S and S represent the number of scenes in original and distorted videos, p, and p" represent the number of frames in f1 scene of original video and / scene of distorted videos respectively, 1