Abstract
The iris health evaluation emphasizes the detecting and analyzing of local variations in the characteristics of irises. Therefore, to accurately extract intestinal loop region of iris and objectively represent the texture feature is a prerequisite for gastrointestinal health evaluation based on iris. Based on the Canny operator approach, this paper presents adaptive Canny operator’s partition for the extracting of intestinal loop region. This paper presents the measurement method of gray level co-occurrence matrix for representing texture information of irregular intestinal loops and the calculating the 6 texture measure. As the input is to establish the support vector machine model, we solve the classification of different kinds of people. Experiments were performed in collected samples. The detection method can effectively extract different types of the iris intestinal loop region. At the same time, the classification model shows that the proposed texture feature works as a measurement of effective health evaluation basis.
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Yuan, W., Huang, J. (2014). Extraction and Analysis of Texture Information of the Iris Intestinal Loop. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_37
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DOI: https://doi.org/10.1007/978-3-319-12484-1_37
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