基于视觉词袋模型的人耳识别

Human Ear Recognition Based on Visual Bag-of-Words Model

人耳识别技术是生物特征识别和人工智能领域的一个重要分支.针对人耳图像特有的纹理特征,首先采用空间金字塔视觉词袋模型进行人耳特征提取,该模型将人耳图像中相对低级的局部描述子特征转化为具有高级语义含义的全局特征.最后采用支持向量机对样本向量进行训练与判别.实验表明,本文所采用的模型能取得较高的识别率,可作为人耳识别方法的一种扩展与探索.

Human ear recognition is one of the most important branches in biometrical recognition and artificial intelligence fields. In this paper, considering the unique texture feature of human ear image, the spatial pyramid visual bag-of-words model was adopted. It transforms the relatively low-level local descriptors of human ear images into global features to preserve the high-level semantic meanings. The support vector machine classifier is utilized to perform the training and recognition task. Experimental results demonstrate that the adopted model could achieve a better accuracy, as an extension and exploration in human ear recognition methods.