面部分层过滤的银行客户识别系统

Bank Customers Recognition System Based on Face Layered Filter

银行客户识别具有深远的意义,在不同的应用场景下可以采用人脸识别算法识别出银行的重要客户.当人脸的特征部位信息发生变化或被掩盖时,人脸识别的精确度会大大降低.本文通过引进面部分层过滤算法,在进行人脸识别之前去除脸部的非特征信息(例如胡子,眼镜,疤等),从而使得人脸识别的处理对象具有更高的统一性.通过MUCI数据集验证了面部分层过滤的可行性,并通过在统一识别模块中加入面部分层过滤算法,提高了识别率,验证了该算法的可行性.

Bank customer identification has a far-reaching significance, which can identify the bank＇s important customers by using face recognition algorithm in different application scenarios. When the feature information of face is changed or masked, the accuracy of recognition will be greatly reduced. The paper introduces the face layered filtering algorithm to remove non characteristic information（such as beard, glasses, scars, etc.） before doing face recognition, so that the face recognition target has a higher unity. By using MUCI data sets to verify the feasibility of facial layered filterer, we add the face layered filtering algorithm in unified recognition module to improve the recognition efficiency. And the feasibility of the algorithm is verified.