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ABSTRACT

TCM's Tongue Diagnosis system promises to deliver a level of uniqueness to diagnosis applications that uses Tongue print, facial scans or recognition to identify users. The tongue is a unique organ in that it can be stuck out of mouth for inspection, in this act offering a proof of life, and yet it is otherwise well protected in the mouth and is difficult to forge. The tongue also presents both geometric shape information and physiological texture information which are potentially useful in identity verification applications. Tongue biometric can function as an extremely reliable means for personal identification and act as a general biometric in all applications. This paper demonstrates two phases. First, find out spots on the tongue with the help of histogram and second phase to extract image tongue and recognize from the tongue-image database.

Keywords: tongue-print; biometric; Histogram; pattern recognition system; Tongue code; Biometrics authentication system, SIFT Feature Extraction.

##1. Introduction

Purpose

– The human tongue is a unique organ that can be stuck out of the body for physical examination, and tongue diagnosis is very important in traditional Chinese medicine. Automated tongue area detection is crucial and indispensable for computer‐aided tongue diagnosis, but it is difficult to implement because of the physiological properties of the tongue. For example, as a non‐rigid organ, the tongue has a high degree of variability in size, shape, color, and texture. The purpose of this study is to address this problem.

##2. Tongue Biometric

To begin with, the tongue is unique to each person in its shape (see Figure 1) and in its surface textures (see Figure 2). Second, the tongue is the only internal organ that can quite normally and easily be exposed for inspection. System design includes the basic architecture, algorithms to be implemented and the flow diagram of the complete system being developed [2]. Matching feature points between images is one of the most fundamental issues in computer vision tasks. Tongue recognition is followed by two Feature of Tongue that is- 2.1 Shape parameter is calculated by using control points which gives the prominent outlines of shape feature of tongue. 2.2 Tongue Texture Feature is calculate by SIFT Algorithm which is Pre-processed by Histogram Equalization.

##3. Shape feature extraction Algorithm (control Points) for Tongue Images

#References:

http://www.emeraldinsight.com/doi/full/10.1108/02602281211197134