Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi
RGB colour variegations are useful features used by the domain's experts in their morphological learning method for skin disease classification. With the advancement of the computer vision technology, not only these features can be quantified in the digital image restoration and enhancement but...
| Main Authors: | , |
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| Format: | Research Reports |
| Language: | English |
| Published: |
Institute of Research, Development and Commercialization, Universiti Teknologi MARA
2004
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/8298/ |
| _version_ | 1848802866005803008 |
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| author | Hashim, Hadzli Abdul Hadi, Razali |
| author_facet | Hashim, Hadzli Abdul Hadi, Razali |
| author_sort | Hashim, Hadzli |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | RGB colour variegations are useful features used by the domain's experts in their morphological learning method for skin disease classification. With the advancement of the computer vision technology, not only these features can be quantified in the digital image restoration and enhancement but also can be used as input parameters of an intelligent diagnostic system. In this report, several psoriasis lesion group are been studied for grayscale color features extraction. The experimental work involved clinical guttate lesion images where they are processed to produce the average Gaussian mean and standard deviation indices using the conventional algorithm. Normal and differential quantified indices gained under controlled environment are then mapped with another set of images from the same and other groups of the psoriasis lesion. The grayscale clustering plots together with each scale index distance from the reference indices are observed and analyzed. Finally, inference statistical tests are applied to conclude the findings. Outcome of the results show only guttate and erythroderma are distinguishable in grayscale mode. |
| first_indexed | 2025-11-14T21:30:09Z |
| format | Research Reports |
| id | uitm-8298 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:30:09Z |
| publishDate | 2004 |
| publisher | Institute of Research, Development and Commercialization, Universiti Teknologi MARA |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-82982023-07-02T23:46:23Z https://ir.uitm.edu.my/id/eprint/8298/ Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi Hashim, Hadzli Abdul Hadi, Razali Skin manifestations of systemic disease Diseases associated with hypersensitivity. Allergic diseases of the skin RGB colour variegations are useful features used by the domain's experts in their morphological learning method for skin disease classification. With the advancement of the computer vision technology, not only these features can be quantified in the digital image restoration and enhancement but also can be used as input parameters of an intelligent diagnostic system. In this report, several psoriasis lesion group are been studied for grayscale color features extraction. The experimental work involved clinical guttate lesion images where they are processed to produce the average Gaussian mean and standard deviation indices using the conventional algorithm. Normal and differential quantified indices gained under controlled environment are then mapped with another set of images from the same and other groups of the psoriasis lesion. The grayscale clustering plots together with each scale index distance from the reference indices are observed and analyzed. Finally, inference statistical tests are applied to conclude the findings. Outcome of the results show only guttate and erythroderma are distinguishable in grayscale mode. Institute of Research, Development and Commercialization, Universiti Teknologi MARA 2004 Research Reports NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/8298/2/8298.pdf Hashim, Hadzli and Abdul Hadi, Razali (2004) Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi. (2004) [Research Reports] <http://terminalib.uitm.edu.my/8298.pdf> (Submitted) |
| spellingShingle | Skin manifestations of systemic disease Diseases associated with hypersensitivity. Allergic diseases of the skin Hashim, Hadzli Abdul Hadi, Razali Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi |
| title | Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi |
| title_full | Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi |
| title_fullStr | Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi |
| title_full_unstemmed | Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi |
| title_short | Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi |
| title_sort | digital segmentation of skin diseases / hadzli hashim and razali abdul hadi |
| topic | Skin manifestations of systemic disease Diseases associated with hypersensitivity. Allergic diseases of the skin |
| url | https://ir.uitm.edu.my/id/eprint/8298/ |