Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41899
Title: | Colour moment method to extract features from endoscopic gastritis digitized images |
Authors: | Nur Thuraiya, Noor Azman Dr. Yasmin Mohd Yacob |
Keywords: | Gastritis Colour moment method Endoscopic digitized image -- Analysis Image classification |
Issue Date: | Jun-2015 |
Publisher: | Universiti Malaysia Perlis (UniMAP) |
Abstract: | Gastritis is a disorder that occur when the stomach lining become swollen, a condition of inflammation or irritation of stomach lining. Normally, visual interpretation or pathology diagnosis is applied to detect any abnormalities in stomach. In this project, computer-aided diagnosis which required image features to classify the endoscopic gastritis digitized image. It is a target to extract features using colour moment method. For image classification, WEKA learning machine is used as multiple classifiers to assort the image into its class of normal or abnormal. Classifier with higher percentage of classification rate is the most accurate. |
Description: | Access is limited to UniMAP community. |
URI: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41899 |
Appears in Collections: | School of Computer and Communication Engineering (FYP) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Abstract,Acknowledgement.pdf | 380.52 kB | Adobe PDF | View/Open | |
Introduction.pdf | 192.17 kB | Adobe PDF | View/Open | |
Literature Review.pdf | 396.39 kB | Adobe PDF | View/Open | |
Methodology.pdf | 734.15 kB | Adobe PDF | View/Open | |
Results and Discussion.pdf | 544.77 kB | Adobe PDF | View/Open | |
Conclusion and Recommendation.pdf | 100.09 kB | Adobe PDF | View/Open | |
Refference and Appendics.pdf | 339.13 kB | Adobe PDF | View/Open |
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