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https://ptsldigital.ukm.my/jspui/handle/123456789/475805Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Siti Norul Huda Sheikh Abdullah, Dr. | - |
| dc.contributor.author | Nor Hanisah Zainal Abidin (P47998) | - |
| dc.date.accessioned | 2023-10-05T06:42:00Z | - |
| dc.date.available | 2023-10-05T06:42:00Z | - |
| dc.date.issued | 2012-03-08 | - |
| dc.identifier.other | ukmvital:120055 | - |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/475805 | - |
| dc.description | Image pattern recognition is widely used in the industries for a lot of purposes such as diagnostic systems, biometrics, military application and optical character recognition (OCR). There are four major steps such as image enhancement, image segmentation, feature extraction, and image classification. The objective of this thesis is to focus on image segmentation process which is one of the important techniques that separates an image into region from the foreground and background of the image. One way to segment such regions is through thresholding process. This simple method is an effective technique to separate objects from the background from gray scale image into binary image. In this research, a multilevel thresholding method is proposed based on combination of maximum entropy. The maximum entropy thresholding algorithm selects several threshold values by maximizing the cross entropy between the original image and the segmented image. This method can effectively integrate partial range of the image histogram. The proposed algorithm is compared with single thresholding method based on maximum entropy and adaptive multi-threshold. The proposed multi thresholding method is tested on license plate application and also five benchmark standard images. From the experiment, multi-threshold method further improved to increase the segmentation accuracy in the future.,Tesis ini tidak ada Perakuan Tesis Sarjana/Doktor Falsafah" | - |
| dc.language.iso | may | - |
| dc.publisher | UKM, Bangi | - |
| dc.relation | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | - |
| dc.rights | UKM | - |
| dc.subject | Biometric system | - |
| dc.subject | Information system | - |
| dc.subject | Universiti Kebangsaan Malaysia -- Dissertations. | - |
| dc.title | Penemberengan imej menggunakan kaedah ambang berasaskan entropi | - |
| dc.type | Theses | - |
| dc.identifier.callno | TK7882.P3N647 2012 3 tesis | - |
| Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
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