A Two-stage CNN Based Computer Vision Framework for Automated Validation of Indian Bank Cheques

Jayadevan R. Kolhe S. Patil P. Pal U. ( 2012 ). ‘ Automatic processing of handwritten bank cheque images: a survey ’. International Journal On Document Analysis And Recognition (IJDAR) , 15 , 267 – 296 .

NIGAM S. Verma S. Nagabhushan P. ( 2023 ). ‘ Document Analysis and Recognition: A survey ’. Authorea Preprints .

Thakur N. Ghai D. Kumar S. ( 2023 ). ‘ Automatic imagery Bank Cheque data extraction based on machine learning approaches: a comprehensive survey ’. Multimedia Tools And Applications , 1 – 56 .

Maity S. Biswas S. Manna S. Banerjee A. Llado’s J. Bhattacharya S. Pal U. ( 2023 ). ‘ Selfdocseg: A selfsupervised vision-based approach towards document segmentation ’. In International Conference On Document Analysis And Recognition ( 342 – 360 .

Fizaine F. Bard P. Paindavoine M. Robin C. Bouye’ E. Lefe`vre R. Vinter A. ( 2024 ). ‘ Historical Text Line Segmentation Using Deep Learning Algorithms: Mask-RCNN against U-Net Networks ’. Journal Of Imaging , 10 , 65 .

Kumar A. Lehal G. ( 2024 ). ‘ Layout Detection of Punjabi Newspapers using the YOLOv8 Model ’. International Journal Of Performability Engineering , 20 .

Affes N. Ktari J. Ben Amor N. Frikha T. Hamam H. ( 2023 ). ‘ Comparison of YOLOV5, YOLOV6, YOLOV7 and YOLOV8 for Intelligent Video Surveillance ’. Journal Of Information Assurance & Security , 18 .

Shaikh A. Mishra K. Kharade P. Kanojia M. ( 2023 ). ‘ Comprehensive Study on Emotion Detection with Facial Expression Images Using YOLO Models ’. Journal Of Information Assurance & Security , 18 .

Palacios R. Gupta A. ( 2008 ). ‘ A system for processing handwritten bank cheques automatically ’. Image And Vision Computing , 26 , 1297 – 1313 .

Miah M. Yousuf M. Mia M. Miya M. ( 2015 ). ‘ Handwritten courtesy amount and signature recognition on bank cheque using neural network ’. International Journal Of Computer Applications , 118 .

Kubik K. Hanmandlu M. Yusof M. Krishna Madasu V. ( 2003 ). ‘ Automatic extraction of signatures from bank cheques and other documents ’. In Proceedings Of The Seventh International Conference On Digital Image Computing: Techniques And Applications, DICTA 2003 .

Dansena P. Kumar K. Pal R. ( 2015 ). ‘ Line based extraction of important regions from a cheque image ’. In 2015 Eighth International Conference On Contemporary Computing (IC3) ( 183 – 189 .

Chandra L. Gupta R. Kumar P. Ganotra D. ( 2008 ). ‘ Automatic courtesy amount recognition for Indian banks’ cheques ’. In TENCON 2008-2008 IEEE Region 10 Conference ( 1 – 5 .

Abdo H. Abdu A. Manza R. Bawiskar S. ( 2023 ). ‘ Extraction of Bank Cheque Fields Based on Faster RCNN ’. In First International Conference On Advances In Computer Vision And Artificial Intelligence Technologies (ACVAIT 2022) ( 130 – 139 .

Agrawal P. Chaudhary D. Madaan V. Zabrovskiy A. Prodan R. Kimovski D. Timmerer C. ( 2021 ). ‘ Automated bank cheque verification using image processing and deep learning methods ’. Multimedia Tools And Applications , 80 , 5319 – 5350 .

Ghosh R. Panda C. Kumar P. ( 2018 ). ‘ Handwritten text recognition in bank cheques ’. In 2018 Conference On Information And Communication Technology (CICT) ( 1 – 6 .

Jha M. Kabra M. Jobanputra S. Sawant R. ( 2019 ). ‘ Automation of cheque transaction using deep learning and optical character recognition ’. In 2019 International Conference On Smart Systems And Inventive Technology (ICSSIT) ( 309 – 312 .

Alirezaee S. Allahiari M. Askari F. Alijamat A. ( 2008 ). ‘ Segmentation of Iranian bank cheques ’. In The International Conference On Electrical Engineering ( 1 – 7 .

Madasu V. Lovell B. ( 2005 ). ‘ Automatic segmentation and recognition of bank cheque fields ’. In Digital Image Computing: Techniques And Applications (DICTA’05) ( 33 – 33 .

Mehta M. Sanchati R. Marchya A. ( 2010 ). ‘ Automatic cheque processing system ’. International Journal Of Computer And Electrical Engineering , 2 , 761 .

Ambikapathy Singh A. ( 2018 ). ‘ Fundamental Concepts of Neural Networks and Deep Learning of Different Techniques to Classify the Handwritten Digits ’. In Advances In Systems, Control And Automation: ETAEERE-2016 ( 287 – 297 .

Chauhan V. Singh S. Sharma A. ( 2024 ). ‘ HCR-Net: A deep learning based script independent handwritten character recognition network ’. Multimedia Tools And Applications , 1 – 35 .

Chaudhary D. Agrawal P. Madaan V. ( 2019 ). ‘ Bank cheque validation using image processing ’. In Advanced Informatics For Computing Research: Third International Conference, ICAICR 2019, Shimla, India, June 15–16, 2019, Revised Selected Papers, Part I 3 ( 148 – 159 .

Poudel U. Regmi A. Stamenkovic Z. Raja S. ( 2023 ). ‘ Applicability of OCR Engines for Text Recognition in Vehicle Number Plates, Receipts and Handwriting ’. Journal Of Circuits, Systems And Computers , 32 , 2350321 .

He K. Gkioxari G. Dolla’r P. Girshick R. ( 2017 ). ‘ Mask r-cnn ’. In Proceedings Of The IEEE International Conference On Computer Vision ( 2961 – 2969 .

Kiatphaisansophon P. Wanvarie D. Cooharojananone N. ( 2024 ). ‘ Efficient Text Bounding Box Identification Using Mask R-CNN: Case of Thai Documents ’. IEEE Access .

Wang Y. Tian S. Wen M. Ruan Y. Tao Q. Zhou X. Gao F. Lu H. Zhang Z. ( 2023 ). ‘ An end- to-end method for palm-leaf manuscript segmentation based on U-Net ’. Journal Of Cultural Heritage , 63 , 169 – 178 .

Nguyen-Trong K. ( 2022 ). ‘ An End-to-End Method to Extract Information from Vietnamese ID Card Images ’. International Journal Of Advanced Computer Science And Applications , 13 .