Anisotropic Gaussian kernels edge detection algorithm based on the chromatic difference

Bin-Bin Su; Mei-Hua Gu; Miao-Miao Wang; Zhi-Lei Wang

doi:10.1117/12.2502846

9 August 2018 Anisotropic Gaussian kernels edge detection algorithm based on the chromatic difference

Bin-Bin Su, Mei-Hua Gu, Miao-Miao Wang, Zhi-Lei Wang

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108062Q (2018) https://doi.org/10.1117/12.2502846
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

The three channels in color images are related to each other, but the edge detection based on gray images tend to ignore the correlation between them. In this paper, we focus on the relationship between every component, highlighting the edge change caused by the color information. Anisotropic Gaussian kernels(ANGKs) edge detection algorithm based on the chromatic difference is proposed in order to improve the performance of edge detection in color images. The proposed algorithm focuses on the chromatic difference among three components. First we derive the color difference S from the gray scale Y and the three channels in RGB color space. Then we use the ANGKs to calculate the gradient magnitude and the direction of S and Y to get S_mag and Y_mag, respectively. The final edges are obtained by double threshold processing after fusing magnitudes of S_mag and Y_mag and non-maximum suppression. We evaluates the performance of the proposed algorithm qualitatively and quantitatively for non-noise images and noise images. The experimental results show that the performance of the proposed algorithm is comparable to other approach.

Citation Download Citation

Bin-Bin Su, Mei-Hua Gu, Miao-Miao Wang, and Zhi-Lei Wang "Anisotropic Gaussian kernels edge detection algorithm based on the chromatic difference", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108062Q (9 August 2018); https://doi.org/10.1117/12.2502846

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