A Hidden Markov Model Scheme for Lip Biometrics Authentication Based on Vertical Grooves Angles

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As the lips move too quickly, the shape of lips images may differ from one situation to another for an individual such as the cases of smiling or frowning.‎ In this paper, we propose a novel approach to automatic classification of lips images which are captured by digital camera.‎ We focus on the lower part of lips based on morphological features of the grooves.‎ Image processing techniques are employed to replace the traditional lipprints to detect human identification with intelligent systems.‎ Presented methodology takes lower part of the lips as an input to process their orientation of grooves.‎ Morphological and structural features are considered to describe the lips.‎ A Hidden Markov Model is proposed for classification and training.‎ Results show the proposed algorithm is robust against scale changes, noises and multiple orientations of lip images for each person.‎ With this approach 93.‎4%, 88.‎3% and 85.‎1% accuracy is achieved in classification of 5, 10, 15 class respectively on 75 lip samples.‎ Presented algorithm may contribute significantly for the development of applications related to human identifications or can be used as a supplement to lip identification systems (for example, methods which are using contour of the lips) to reduce the error rate of classification.‎

تاریخ انتشار: 
يكشنبه, ۱۹ فروردين, ۱۳۹۷ - ۰۸
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