potato image segmentation is an important part of image-based potato defect detection. this paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on genetic algorithm (ga) optimization and morphological operators. the proposed potato color image segmentation is robust against variation of background, distance and ...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

background: nowadays, analyzing human facial image has gained ever-increasing importance due to its various applications. image segmentation is required as a very important and fundamental operation for significant analysis and interpretation of images. methods: among the segmentation methods, image thresholding technique is one of the most well-known methods due to its simplicity, robustness a...

Image segmentation is the technique in which an image into meaningful parts .It plays an important role in the image analysis and computer version. GA algorithm are evolutionary in nature so, it proved to be very time consuming. So, to overcome the limitation of the GA based on the multilevel thresholding, Ant Colony based Optimization on multilevel thresholding segmentation algorithm will be p...

Entropy-based image thresholding are used widely in image processing. Conventional methods are efficient in the case of bilevel thresholding. But they are very computationally time consuming when extended to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. In this paper, we propose a conditional probability entropy (CPE) based on...

Multilevel thresholding is a method that is widely used in image segmentation. The thresholding problem is treated as an optimization problem with an objective function. In this article, a simple and histogram based approach is presented for multilevel thresholding in image segmentation. The proposed method combines Tsallis objective function and Particle Swarm Optimization (PSO). The PSO algor...

Image segmentation is a basic work in the field of image analysis and computer vision. Thresholding is one of the simplest methods of image segmentation. In general, thresholding approaches based on 1-D histogram do not make use of any space adjacent information of the image, thus it is often ruined by noise; thus, thresholding methods based on 2-D histogram are put forward. These methods have ...

due to damaging effects of speckle noise to information of radar images, reduction of these effects has been considered by many researchers. we discussed speckle reduction of radar images based on curvelet transformation. more specifically we discussed the speckle reduction with emphasizing on preservation of the edges by hard thresholding of curvelet transformation. in this algorithm, first mu...