基于皮肤颜色和模板的耳朵自动检测技术

S. Prakash, U. Jayaraman, Phalguni Gupta
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引用次数: 50

摘要

本文提出了一种有效的基于肤色和模板的侧脸图像耳朵自动检测技术。该技术首先将皮肤区域与非皮肤区域分开,然后在皮肤区域内搜索耳朵。耳朵检测过程包括三个主要步骤。首先进行皮肤分割,消除图像中所有非皮肤像素;其次进行耳朵定位,使用模板匹配方法进行耳朵检测;第三进行耳朵验证,使用基于Zernike矩的形状描述符验证耳朵检测。为了处理各种形状和大小的耳朵检测,考虑各种形状(三角形、圆形、椭圆形和矩形)的耳朵创建一个耳朵模板,并自动调整大小为适合检测的大小。在印度理工学院坎普尔分校的150张侧脸图像的耳朵数据库上进行了测试,准确率达到94%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Skin-Color and Template Based Technique for Automatic Ear Detection
This paper proposes an efficient skin-color and template based technique for automatic ear detection in a side face image. The technique first separates skin regions from non skin regions and then searches for the ear within skin regions. Ear detection process involves three major steps. First, Skin Segmentation to eliminate all non-skin pixels from the image, second Ear Localization to perform ear detection using template matching approach, and third Ear Verification to validate the ear detection using the Zernike moments based shape descriptor. To handle the detection of ears of various shapes and sizes, an ear template is created considering the ears of various shapes (triangular, round, oval and rectangular) and resized automatically to a size suitable for the detection. Proposed technique is tested on the IIT Kanpur ear database consisting of 150 side face images and gives 94% accuracy.
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