| Paper Details: | Downloads: 416 |
| Serial Number: | P1150905607
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| Title: | Automatic Segmentation Technique for Color Images
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| Authors: | Jun Zhangyy and Jinglu Hu
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| Abstract: | based on self-organizing feature map (SOFM) neural network (NN) is presented for color images. First, a binary tree clustering procedure is used to cluster the colors in an image. In each node of the tree, a SOFM NN is used as a classifier which is fed by image color values. The output neurons of the SOFM NN define the color classes for each node. In proposed method, the number of color classes for each node is two. For each node of the tree, Hotelling transform based class condition is used to define if the current color classes need to be classified. To speed up the entire algorithm, a nearest neighbor interpolation is used to get the small training set for SOFM NN. Once the colors in an image are clustered, it is easy to segment the target by analyzing the representing colors. The method is independent of the color scheme, which means that it is applicable to any type of color images. The experimental results show the validity of the proposed method.
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| Keywords: | Color Clustering, Color Image Segmentation, Self-Organizing Feature Map (SOFM), Neural Network(NN), Image Rearrangement.
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| Journal/Conference: | International Journal of Graphics, Vision and Image Processing
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| Volume: | 9
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| Issue: | 3
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| Submission Date: | 1/29/2009 12:00:00 AM
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| Review Date: | 2/8/2009 12:00:00 AM
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| Publishing Date: | 4/9/2009 12:00:00 AM
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| Article Downloads: | 416
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