dc.contributor.author | KHAJA MOINUDDIN, SIDDIQUI MOHAMMED | |
dc.contributor.author | Jain, Dr. Arvind Kumar (Supervisor) | |
dc.contributor.author | Ahmed, Dr. Sayeed (Co supervisor) | |
dc.contributor.author | Kumar, Dr. Suneet (Co supervisor) | |
dc.date.accessioned | 2023-11-22T05:26:25Z | |
dc.date.available | 2023-11-22T05:26:25Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://10.10.11.6/handle/1/12196 | |
dc.description.abstract | Handwriting 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.iso | en_US | en_US |
dc.publisher | GALGOTIAS UNIVERSITY | en_US |
dc.subject | FORENSIC SCIENCE, HANDWRITING, AMBIDEXTROUS PERSON, Both hands | en_US |
dc.title | STUDY ON HANDWRITING FEATURES OF AMBIDEXTROUS PERSONS | en_US |
dc.title.alternative | STUDY ON HANDWRITING FEATURES OF AMBIDEXTROUS PERSONS | en_US |
dc.type | Thesis | en_US |