Segmentation of nontrivial images is one of the most important tasks in image processing. It is easy for human being, but extremely difficult for computers. With the purpose of finding optimal segmentation algorithm for every image through learning from human experience, this paper investigates the
โฆ LIBER โฆ
Image segmentation based on competitive learning
โ Scribed by Jing Zhang; Qun Liu; Nath Baikunth
- Publisher
- Harbin Engineering University
- Year
- 2004
- Tongue
- English
- Weight
- 948 KB
- Volume
- 3
- Category
- Article
- ISSN
- 1671-9433
No coin nor oath required. For personal study only.
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We present an image segmentation system specifically targeted for oil sand ore size estimation. The system learns spectral and shape characteristics of training images of oil sand ore samples for image quality enhancement followed by segmentation of ore image shapes. The proposed segmentation has ac