dc.contributor.author | Trongtirakul, Thaweesak | en_US |
dc.contributor.author | Phanthuna, Nattapong | en_US |
dc.contributor.author | Disklud, Nikom | en_US |
dc.contributor.author | ทวีศักดิ์ ตรงติรกุล | en_US |
dc.contributor.author | ณัฐพงศ์ พันธุนะ | en_US |
dc.contributor.author | นิคม ดิษฐคลึ | en_US |
dc.date.accessioned | 2018-02-13T11:08:06Z | |
dc.date.available | 2018-02-13T11:08:06Z | |
dc.date.issued | 2017-07-02 | |
dc.identifier.uri | http://repository.rmutp.ac.th/handle/123456789/2303 | |
dc.description | รายงานวิจัย -- มหาวิทยาลัยเทคโนโลยีราชมงคลพระนคร, 2558 | en_US |
dc.description.abstract | The segmentation of interesting objects within the image is an important process to provide information for other procedures. The major problem of image segmentation is the number of objects suitable for classifying objects. This research aims to present on Image Segmentation using Fuzzy C- Mean Via Image Filter. The objects will be split up using their object intensities. The proposed method can classify several objects at the same process. Therefore, it saves time to process less than other existing methods. The proposed method is consisted of three steps: noise reduction, histogram smoothing and object classification. The results of the proposed method found that objects are automatically classified by Fuzzy C-Mean. Moreover, the algorithm that successfully calculates the proper number of segmentations | en_US |
dc.description.sponsorship | Rajamangala University of Technology Phra Nakhon | en_US |
dc.subject | Fuzzy C-Mean | en_US |
dc.subject | Gaussian Filter | en_US |
dc.subject | Image Segmentation | en_US |
dc.title | Image Segmentation Using Fuzzy C-Mean Via Image Filter | en_US |
dc.type | Research Report | en_US |