Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin
Image enhancement methods are widely used in a variety of picture processing applications where image subjective quality is vital for human interpretation. In any subjective assessment of image quality, contrast is critical. The difference in brightness reflected from two nearby surfaces creates it....
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التنسيق: | أطروحة |
اللغة: | English |
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2022
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الوصول للمادة أونلاين: | https://ir.uitm.edu.my/id/eprint/59316/2/59316.pdf |
الوسوم: |
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my-uitm-ir.593162023-12-18T04:00:38Z Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin 2022 Shammudin, Izzah Atirah Electronic Computers. Computer Science Configuration management Code generators Image enhancement methods are widely used in a variety of picture processing applications where image subjective quality is vital for human interpretation. In any subjective assessment of image quality, contrast is critical. The difference in brightness reflected from two nearby surfaces creates it. Contrast, in particular, is the distinction in visual qualities that makes an item identifiable from other objects as well as the background. Contrast is defined visually by the separation between the colors and brightness of the objects. Several techniques for producing contrast enhancement are being developed and applied to image processing. “Once the image of a handwritten signature for a customer is captured, several pre-processing steps are performed on it including filtration and detection of the signature edges.” (Hussein, Salama, & Ibrahim, 2016) 2022 Thesis https://ir.uitm.edu.my/id/eprint/59316/ https://ir.uitm.edu.my/id/eprint/59316/2/59316.pdf text en public degree Universiti Teknologi MARA, Perak Faculty of Computer and Mathematical Sciences Darmawan, Mohd Faaizie |
institution |
Universiti Teknologi MARA |
collection |
UiTM Institutional Repository |
language |
English |
advisor |
Darmawan, Mohd Faaizie |
topic |
Electronic Computers Computer Science Configuration management Code generators |
spellingShingle |
Electronic Computers Computer Science Configuration management Code generators Shammudin, Izzah Atirah Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin |
description |
Image enhancement methods are widely used in a variety of picture processing applications where image subjective quality is vital for human interpretation. In any subjective assessment of image quality, contrast is critical. The difference in brightness reflected from two nearby surfaces creates it. Contrast, in particular, is the distinction in visual qualities that makes an item identifiable from other objects as well as the background. Contrast is defined visually by the separation between the colors and brightness of the objects. Several techniques for producing contrast enhancement are being developed and applied to image processing. “Once the image of a handwritten signature for a customer is captured, several pre-processing steps are performed on it including filtration and detection of the signature edges.” (Hussein, Salama, & Ibrahim, 2016) |
format |
Thesis |
qualification_level |
Bachelor degree |
author |
Shammudin, Izzah Atirah |
author_facet |
Shammudin, Izzah Atirah |
author_sort |
Shammudin, Izzah Atirah |
title |
Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin |
title_short |
Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin |
title_full |
Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin |
title_fullStr |
Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin |
title_full_unstemmed |
Handwritten signature recognition for forgery detection / Izzah Atirah Shammudin |
title_sort |
handwritten signature recognition for forgery detection / izzah atirah shammudin |
granting_institution |
Universiti Teknologi MARA, Perak |
granting_department |
Faculty of Computer and Mathematical Sciences |
publishDate |
2022 |
url |
https://ir.uitm.edu.my/id/eprint/59316/2/59316.pdf |
_version_ |
1794191834176552960 |