COLOR IMAGE EDGE DETECTION BASED ON QUANTITY OF COLOR INFORMATION AND ITS IMPLEMENTATION ON THE GPU

In this paper, we present a new method for quantifying color information so as to detect edges in color images. Our method uses the volume of a pixel in the HSI color space, allied with noise reduction, thresholding and edge thinning. We implement our algorithm using NVIDIA Compute Unified Device Architecture (CUDA) for direct execution on Graphics Processing Units (GPUs). Our experimental results show that: compared to traditional edge detection methods, our method can improve the accuracy of edge detection and withstand greater levels of noise in images; and our GPU implementation achieves speedups over related CUDA implementations.

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