In this paper we present a new image thresholding method based on a multiobjective Genetic Algorithm using the Pareto optimality approach. We aim to optimize multiple criteria in order to increase the segmentation quality. Thus, we’ve adapted the well known Non Domination Sorting Genetic Algorithm for this purpose so that it takes into consideration the contribution of the objective functions i...

Image processing plays an important role in computer vision. The process of image segmentation provides the partition of image into different segments according to their feature attribute. Region based segmentation is a type similarity based segmentation. Another type of segmentation is called thresholding based segmentation. In thresholding based segmentation method some thresholding technique...

Image thresholding is well accepted and one of the most imperative practices to accomplish image segmentation. This has been widely studied over the past few decades. However, as the multi-level thresholding computationally takes more time when level increases, hence, in this article, quantum mechanism is used to propose six different quantum inspired meta-heuristic methods for performing multi...

In large-scale digitization processes, several common tasks are performed to provide an electronic version of a paper document. One of the first steps is the thresholding of the image, which is necessary for the following procedures to work properly. Many binarization methods have been proposed to solve this problem, but they need to be tuned on the target document corpus to obtain best results...

Abstract In order to select for image thresholding an optimal threshold that is relatively robust to the presence of skew or heavy-tailed class-conditional distributions, we propose in this paper two median-based approaches: one is an extension of Otsu’s method, and the other is an extension of Kittler and Illingworth’s minimum error thresholding. The two extensions preserve the methodological ...

Automatic mineral identification using evolutionary computation technology is discussed. Thin sections of mineral samples are digitally photographed using a computercontrolled rotating polarizer stage on a petrographic microscope. A suite of image processing functions is applied to the images. Filtered image data for identified mineral grains is then selected for use as training data for a gene...

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 ...

In this paper, An Automatic Multilevel Thresholding Method for Image segmentation is proposed based on Discrete Wavelet Transforms and Genetic Algorithm. We have combined Genetic Algorithm with DWT to make Segmentation faster and adequate results. First the length of the histogram is reduced by using DWT. Using this Reduced Histogram, the number of Thresholds and Threshold Value are determined ...