使用相机和ARM 11进行嘴唇特征检测

Sigit Wasista, Setiawardhana, Firman Zaenur Rochim
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引用次数: 1

摘要

本研究旨在利用唇角检测进行简单的唇特征识别。这种特征检测从搜索人脸区域开始,利用皮肤分割继续通过人体测量一般人脸来寻找嘴唇区域。然后从待搜索的嘴唇区域出发,利用唇角检测算法通过最小灰度值结合积分投影确定嘴角的坐标。使用11张人脸进行特征检测测试,每张人脸实时呈现四种不同的表情。正常情况下的四种表情,瘦弱的微笑,灿烂的微笑和凝视代表即将到来的噪音的可能性,以确保嘴唇特征检测系统的准确性。从测试结果中获得该系统正常状态下的平均成功率为77.9%,细笑91.68%,宽笑95.97%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lips feature detection using camera and ARM 11
This study aims to perform a simple lips feature recognition using lips angle detection. This feature detection starts from the search area of the face using skin segmentation continues to find the area of the lips by anthropometry human face in general. Then from the lips area to be searched its use lips angle detection algorithm to determine the coordinates of the corner of his mouth by the Lowest grayscale value combined with integral projections. Testing feature detection using 11 human faces, each doing four different expressions performed in real time. Four expressions are normal conditions, a thin smile, big smile and stare representing the possibilities of impending noise to ensure the accuracy of the lips features detection system. From the test results Obtained an average percentage of success of the system to normal conditions of 77.9%, a thin smile 91.68%, 95.97% and a wide smile.
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