Abstract
It is difficult to separate the foreign fiber objects in a captured color image from the background accurately. To solve this problem, this paper presents a new approach for color image segmentation in RGB color space based on color saliency. Firstly, the captured RGB color image was separated to R, G and B color channels, and the color information for each channel was calculated. Secondly, the R saliency for each pixel in the R channel, the G saliency for each pixel in the G channel, and the B saliency for each pixel in the B channel was calculated respectively. Then comprehensive saliency map was obtained by the weighted R, G and B saliency. The weights for the R, G and B saliency were determined by the corresponding color information of each color channel. At last, the foreign fiber targets were separated out from the comprehensive saliency map using a threshold method. The results indicate that the proposed method can segment out the foreign fiber objects from the color image accurately.
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Yang, W.Z., Li, D.L., Wei, X.H., Kang, Y.G., Li, F.T.: An automated visual inspection system for foreign fiber detection in lint. In: IEEE GCIS, pp. 364–368 (2009)
Yang, W., Lu, S., Wang, S., Li, D.: Fast recognition of foreign fibers in cotton lint using machine vision. Mathematical and Computer Modelling 54, 877–882 (2011)
Yang, W.-Z., Li, D.-L., Zhu, L.: A New Approach for Image Processing in Foreign Fiber Detection. Computers and Electronics in Agriculture 68(1), 68–77 (2009)
Yang, W., Li, D., Wang, S., Lu, S., Yang, J.: Saliency map basee color image segmentation for foreign fiber detection. Mathematics and Computer Modelling 58, 846–852 (2013)
Ye, Q.-X., Wen, G., Wang, W.-Q., et al.: A Color Image Segmentation Algorithm by Using Color and Spatial Information. Journal of Software 15(4), 522–530 (2004)
Bao, Q.-L.: Color Image Segmentation Based on HSV Color Space. Software Guide 9(7), 171 (2010)
Zhao, J.-X., Wang, J.: Color I mage Edge Detection Based on Subdivision of RGB Space. Optoelectronic Technology 29(3), 171–173 (2009)
Han, X.-W., Yang, Z., Li, Y.-P., et al.: A Method for Color Image Segmentation Based on Color Similarity Coefficient. Journal of Shenyang University 26(6), 14–17 (2004)
Zhang, H.-W., Zheng, Y.-F., Zhang, Q.-R.: Color Image Segmentation Based on Visual Attention Mechanism. Computer Engineer and Application 47(10), 154–157 (2011)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)
Hou, X.-D., Zhang, L.-Q.: Saliency Detection: A Spectral Residual Approach. In: Proceedings of The IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)
Stas, G., Lihi, Z.-M., Ayellet, T.: Context-Aware Saliency Detection. IEEE Transactions Pattern Analysis and Machine Intelligence 34(10), 1915–1926 (2012)
Shi, H., Yang, Y.: A Computational Model of Visual Attention Based on Saliency Maps. Applied Mathematics and Computation 188, 1671–1677 (2007)
Hang, S., Yu, Y.: A computational model of visual attention based on saliency maps. Applied Mathematics and Computation 18(2), 1671–1677 (2007)
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Zhang, C., Yang, W., Liu, Z., Li, D., Chen, Y., Li, Z. (2014). Color Image Segmentation in RGB Color Space Based on Color Saliency. In: Li, D., Chen, Y. (eds) Computer and Computing Technologies in Agriculture VII. CCTA 2013. IFIP Advances in Information and Communication Technology, vol 419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54344-9_41
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DOI: https://doi.org/10.1007/978-3-642-54344-9_41
Publisher Name: Springer, Berlin, Heidelberg
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