A color extraction algorithm by segmentation

被引:0
作者
QingE Wu
Zhenggaoyuan Fang
Zhichao Song
Hu Chen
Yingbo Lu
Lintao Zhou
Xiaoliang Qian
机构
[1] Zhengzhou University of Light Industry,School of Electrical and Information Engineering
来源
Scientific Reports | / 13卷
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摘要
The segmentation and extraction on color features can provide useful information for many different application domains. However, most of the existing image processing algorithms on feature extraction are gray image-based and consider only one-dimensional parameters. In order to carry out a fast and accurate color feature extraction, this paper proposes a color extraction algorithm by segmentation that is called a color extraction algorithm This algorithm is compared under different color distribution situations, and the extraction effect on color is also shown by the combination of the segmentation and feature extraction algorithms. Experimental results show that such segmentation algorithm has some advantages for color segmentation. In the fuzzy color image preprocessing, this paper gives the location method of region of interest. Moreover, compared with other existing extraction algorithms, the presented segmentation extraction algorithm in this paper not only has higher accuracy, shorter extraction time and stronger anti-interference ability, but also has better effect on more divergent color edge. Experimental evaluation of the proposed color extraction algorithm demonstrates dominance over existing algorithms for feature extraction. These researches in this paper provide a new way of thinking for color feature extraction by segmentation, which has an important theoretical references and practical significance.
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[1]  
Ziyu H(2023)Canny algorithm enabling precise offline line edge roughness acquisition in high-resolution lithography [J] ACS Omega 8 3992-3997
[2]  
Rongbo Z(2023)Image watermarking using least significant bit and canny edge detection [J] Sensors 23 1210-677
[3]  
Xiaolin W(2023)Edge detection using guided sobel image filtering [J] Wirel. Pers. Commun. 132 651-9770
[4]  
Bin ZF(2023)Sobel edge detection algorithm with adaptive threshold based on improved genetic algorithm for image processing [J] Int. J. Adv. Comput. Sci. Appl. 14 1-29983
[5]  
Abid I(2022)Edge detection on noisy images using Prewitt operator and fractional order differentiation [J] Multimed. Tools Appl. 81 9759-39
[6]  
Furqan R(2021)Design of Fractional Calculus based differentiator for edge detection in color images Multimed. Tools Appl. 80 29965-2070
[7]  
Rakesh R(2022)Subpixel edge detection algorithm based on improved Gaussian fitting and Canny operator[J] Acad. J. Comput. Inf. Sci. 5 33-209
[8]  
Vinay A(2023)Simulation and implementation of two-layer oscillatory neural networks for image edge detection: Bidirectional and feedforward architectures[J] Neuromorph. Comput. Eng. 3 1-128
[9]  
Kong W(2023)Research on image denoising in edge detection based on wavelet transform[J] Appl. Sci. 13 2061-1239
[10]  
Chen J(2020)An improved industrial sub-pixel edge detection algorithm based on coarse and precise location J. Ambient Intell. Hum. Comput. 11 206-28