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@article{167694,
        author = {Mallikarjun Anandhalli and Anup Ritti and Pavana Baligar and Chandrakant Naikodi},
        title = {Automatic Check Processing System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {4},
        pages = {83-89},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167694},
        abstract = {Automatic Cheque Processing, it is one of the most studied areas of the 0alysis of documents and biometric data. In this area, several methods are proposed for the Automatic Cheque Processing and forgery detection. Sometimes an account holder gives self-cheques to another person. Some persons provided a self-cheque to him/her by counterfeiting signature of another person. Due to the us can observe significant rise in forgery cases. In this paper, we propose a mechanism for the recognition of the fields of the cheque, such as first name, last name, and the amount, as well as how to verify the signature, and the authenticity of it. We propose a unique two-stage model of automatic cheque processing with the detection of skilled forgery of the signature by pre-processing of the image of the cheque, segmentation, and feature extraction. It was found that the nature of the risk, the precision and accuracy of 95%, the character recognition (OCR) is the efficiency of 83%, the number of recognition efficiency of 91% or more, and the system will detect the forgery, with an accuracy of 80% to detect signature, with an accuracy of 91%.},
        keywords = {Forgery detection, authenticity, segmentation, ACS, feature extraction, efficiency, accuracy.},
        month = {September},
        }