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In this paper, a hybrid of mean-shift and median-cut algorithm was introduced to perform segmentation on color images. Firstly, the image pre-processing technique was applied to enhance the image before changing the color space to LUV color space. Then mean-shift segmentation was introduced. However, some region has no semantic meaning since the mean-shift algorithm performed low level segmentation...
In this paper, we describe algorithms that perform fuzzy clustering and feature weighting simultaneously and in an unsupervised manner. These algorithms are conceptually and computationally simple, and learn a different set of feature weights for each identified cluster. The cluster dependent feature weights offer two advantages. First, they guide the clustering process to partition the data into...
One of the most famous approaches for the segmentation of color images is finding clusters in the color space. Shapes of these clusters are often complex and the time complexity of the existing algorithms for finding clusters of different shapes is usually high. In this paper, a novel clustering algorithm is proposed and used for the image segmentation purpose. This algorithm distinguishes clusters...
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