Image edge detection algorithms using color models
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Edge detection is one of the fundamental tasks in image analysis. Proposed research work highlights the detection of edges of each layer separately through Sobel/Laplacian operators and concatenating them with the other layers. This approach gives better results in detecting edges when compared with the existing methods. The original image is transformed to other color models to extract the features effectively. The different color models used in the proposed work are RGB (Red, Green, Blue), YCbCr (Y-Luma, Cb - Blue difference and Cr-Red Difference Chrominance), YUV (Y-Luma, U - Blue differenc...
Edge detection is one of the fundamental tasks in image analysis. Proposed research work highlights the detection of edges of each layer separately through Sobel/Laplacian operators and concatenating them with the other layers. This approach gives better results in detecting edges when compared with the existing methods. The original image is transformed to other color models to extract the features effectively. The different color models used in the proposed work are RGB (Red, Green, Blue), YCbCr (Y-Luma, Cb - Blue difference and Cr-Red Difference Chrominance), YUV (Y-Luma, U - Blue difference and V-Red Difference Chrominance) and XYZ (Y-Luminance, Z - Blue difference and X-Red Difference Chrominance).The main concept of proposed research work is to develop an algorithm which is device/machine independent to extract the edge detection features using different color models.
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