Image Segmentation Using Variable Kernel Fuzzy C Means (VKFCM) Clustering on Modified Level Set Method
| Autor: | B. Venkata Shiva Reddy, Md. Ameen Uddin, Khaja FasiUddin, Tara Saikumar |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Fuzzy clustering
business.industry Computer science Segmentation-based object categorization ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Pattern recognition Image segmentation Fuzzy logic Kernel (image processing) Indicator function Variable kernel density estimation Computer Science::Computer Vision and Pattern Recognition Artificial intelligence business |
| Zdroj: | Lecture Notes in Electrical Engineering ISBN: 9781461461531 |
| DOI: | 10.1007/978-1-4614-6154-8_26 |
| Popis: | In this paper, Variable Kernel Fuzzy C-Means (VKFCM) was used to generate an initial contour curve which overcomes leaking at the boundary during the curve propagation. Firstly, VKFCM algorithm computes the fuzzy membership values for each pixel. On the basis of VKFCM the edge indicator function was redefined. Using the edge indicator function the image segmentation of a medical image was performed to extract the regions of interest for further processing. The above process of segmentation showed a considerable improvement in the evolution of the level set function. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|