Abstract
Recognition of petechia tongue is still a challenging problem due to different color, morphology and texture in tongue image. This paper presents a new method to automatically recognition of petechia tongue based on LoG and Gabor feature with spatial information. The proposed approach begins with a normalized LoG filter to locate the suspected petechia areas in tongue image. In the subsequent step, the spatial position feature and Gabor feature were extracted as a feature descriptor of these regions. Support vector machine is used as a classifier to classify these suspected petechia areas into petechia and non-petechia areas. Finally, the proposed method judge whether the tongue image have petechia according to the proportion of petechia regions to all suspected petechia regions. Experimental results on two hundred tongue images indicate the better performance of our method, the accuracy achieves to 84.91%.
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Zhao, Y., Li, X., Fu, Z. (2012). Recognition of Petechia Tongue Based on LoG and Gabor Feature with Spatial Information. In: Zheng, WS., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds) Biometric Recognition. CCBR 2012. Lecture Notes in Computer Science, vol 7701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35136-5_38
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DOI: https://doi.org/10.1007/978-3-642-35136-5_38
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