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For the robot vision system in apple harvesting robot, a new image segmentation method based on entropy clustering is proposed in HSI color space. Firstly, noise was wiped off by using weighted algorithm of median filtering in HSI color space instead of traditional algorithm in RGB model; secondly, Hue and Saturation components were extracted to do entropy clustering with their independence with Intensity,...
Detection of brain tumors from MRI is a time consuming and error-prone task. This is due to the diversity in shape, size and appearance of the tumors. In this paper, we propose a clustering algorithm based on Particle Swarm Optimization (PSO). The algorithm finds the centroids of number of clusters, where each cluster groups together brain tumor patterns, obtained from MR Images. The results obtained...
This paper addresses a novel issue of intuitionistic fuzzy c means color clustering using intuitionistic fuzzy set theory. The intuitionistic fuzzy set theory takes into the membership degree and non membership degree. Non membership degree is calculated from Sugeno type intuitionistic fuzzy complement. The introduction of another uncertainty term i.e. the non membership degree helps to converge the...
It has been well documented that radiologists' performance is not perfect: they make both false positive and false negative decisions. For example, approximately thirty percent of early lung cancer is missed on chest radiographs when the evidence is clearly visible in retrospect. Currently computer-aided detection (CAD) uses software, designed to reduce errors by drawing radiologists' attention to...
Several general-purpose algorithms and techniques have been developed for image segmentation. Since there is no general solution to the image segmentation problem, these techniques often have to be combined with domain knowledge in order to effectively solve an image segmentation problem for a problem domain. This paper presents a comparative study of the basic image segmentation techniques i.e. edge-based,...
This paper presents a method to design programming system using hybrid techniques represented by soft computing to classify objects from the air photos and satellite images depending on their features with minimum acceptable error. These images usually consist of seven layers, while the work in this research focuses on dealing with three bands (red, green and blue). This paper concerns with classifying...
Forward looking infrared (FLIR) image segmentation is crucial for automatic target recognition (ATR). This paper presents a new clustering algorithm for FLIR image segmentation. We combine the standard fuzzy c-means algorithm (FCM) with two-dimensional histogram of the image, and modify the membership function of the FCM for taking into account the spatial information of image data. Since the FCM...
We describe an exploratory technique based on the direct interaction with a 2D modified scatterplot computed from two different metrics calculated over the elements of a network. The scatterplot is transformed into an image by applying standard image processing techniques resulting into blurring effects. Segmentation of the image allow to easily select patches on the image as a way to extract subnetworks...
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