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dc.contributor.authorKHAJA MOINUDDIN, SIDDIQUI MOHAMMED
dc.contributor.authorJain, Dr. Arvind Kumar (Supervisor)
dc.contributor.authorAhmed, Dr. Sayeed (Co supervisor)
dc.contributor.authorKumar, Dr. Suneet (Co supervisor)
dc.date.accessioned2023-11-22T05:26:25Z
dc.date.available2023-11-22T05:26:25Z
dc.date.issued2022
dc.identifier.urihttp://10.10.11.6/handle/1/12196
dc.description.abstractHandwriting recognition is a fascinating and convincing piece of writing because everybody has his or her own writing style in this world. The most challenging part is determining the unique qualities of each word's handwriting. It is observed that Predicting and implementing handwriting paragraph feature data is difficult, therefore data pre-processing is required. Pre-processing, differentiation, description, preparation, identification and post-processing are some important steps involved in handwritten character recognition. For implementation, Python and the deep learning programming language were used. Hand writing recognition is an important procedure that enables handwritten inputs, including touch screen, papers, photographs and other devices, to be gathered and understood. The pictures of written texts in optical image processing are named as "off line." It is easier to describe the "on-line" behaviour of a pen's tip on a pen-based gadget since more options are available. The key method of recognition of optical character is the handwriting detection.en_US
dc.language.isoen_USen_US
dc.publisherGALGOTIAS UNIVERSITYen_US
dc.subjectFORENSIC SCIENCE, HANDWRITING, AMBIDEXTROUS PERSON, Both handsen_US
dc.titleSTUDY ON HANDWRITING FEATURES OF AMBIDEXTROUS PERSONSen_US
dc.title.alternativeSTUDY ON HANDWRITING FEATURES OF AMBIDEXTROUS PERSONSen_US
dc.typeThesisen_US


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