Abstract
Aiming at the problems existing in traditional color image segmentation methods, namely, image noise and image quality are poor, a color image automatic segmentation method based on visual characteristics is proposed. The method first analyzes the human visual characteristics, then uses the weighted average method to grayscale the color image, then uses the histogram equalization method to enhance the image, and then detects the edge of the image through the binary wavelet, and finally in the image. Image segmentation based on edge detection. The results show that compared with the traditional image segmentation method, the segmented color image of this method has a SNR of 5.3 dB, less noise and improved image quality.
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Hongya, Y., Jingxiu, Z., Guanhua, X., et al.: A survey of color image segmentation methods. Softw. Guide 17(4), 1–5 (2018)
Anonymous. Explore the application of computer image segmentation algorithm based on visual characteristics. Comput. Program. Skills Maintenance, 401(11), 144–154 (2018)
Marlowe. Research on graphic image segmentation algorithms based on visual characteristics. Comput. Knowl. Technol. 14(17), 222–223 (2018)
Jie, Z., Hongxia, P., Mingjun, T.: An image perception method for crop diseases based on machine vision features. Agric. Technol. 37(18), 11–13 (2017)
Liu, S., Lu, M., Li, H., et al.: Prediction of gene expression patterns with generalized linear regression model. Front. Genetics 10, 120 (2019)
Yuelin, G.L., et al.: Image enhancement algorithm based on histogram segmentation coupled with clipping control equalization. Comput. Eng. Des. (2) 465–469 (2017)
Xinchun, L., Shidong, C., Moyan, Z., et al.: Edge detection of contrast images based on local histogram correlation. Chin. J. Image Graph. 5(9), 750–754 (2018)
Zhiguo, Z., Qian, Z., Jingchuan, L.: Image edge detection based on interpolation wavelet tower decomposition. Comput. Sci. 44(s1), 164–168 (2017)
Feng, J., Qing, G., Huizhen, H., et al.: A review of content-based image segmentation methods. J Softw. 28(1), 160–183 (2017)
Zheng, P., Shuai, L., Arun, S., Khan, M.: Visual attention feature (VAF): a novel strategy for visual tracking based on cloud platform in intelligent surveillance systems. J. Parallel Distrib. Comput. 120, 182–194 (2018)
Liu, S., Liu, D., Srivastava, G., et al.: Overview and methods of correlation filter algorithms in object tracking. Complex Intell. Syst. (2020). https://doi.org/10.1007/s40747-020-00161-4
Mengye, L., Shuai, L.: Nucleosome positioning based on generalized relative entropy. Soft. Comput. 23, 9175–9188 (2019)
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Wang, J., Gao, J. (2021). Automatic Color Image Segmentation Based on Visual Characteristics in Cloud Computing. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 348. Springer, Cham. https://doi.org/10.1007/978-3-030-67874-6_27
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DOI: https://doi.org/10.1007/978-3-030-67874-6_27
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