Face recognition using viola-jones depending on python
نویسندگان
چکیده
منابع مشابه
Detection of Face using Viola Jones and Recognition using Back Propagation Neural Network
Detection and recognition of the facial images of people is an intricate problem which has garnered much attention during recent years due to its ever increasing applications in numerous fields. It continues to pose a challenge in finding a robust solution to it. Its scope extends to catering the security, commercial and law enforcement applications. Research for moreover a decade on this subje...
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In this paper, an automatic face recognition system is proposed based on appearance-based features that focus on the entire face image rather than local facial features. The first step in face recognition system is face detection. Viola-Jones face detection method that capable of processing images extremely while achieving high detection rates is used. This method has the most impact in the 200...
متن کاملFace Recognition and Detection using Viola-Jones and Cross Correlation Method
The face detection is process of detecting region of face from a picture of one or multiple persons together. The detected face is extracted in the proposed using the viola-Jones algorithm. The viola-Jones algorithm is considered effective in order to mark and extract the face features. The proposed model is using the correlation model for the purpose of the face recognition. The face recogniti...
متن کاملReview of Literature Face Detection via Viola Jones
Face recognition has been one of the most studied topics in the last decades. Its research has increased in many applications in communications and automatic access control systems. In this paper, a new face recognition method based on face detection technique is introduced. The goal of the propose method is to detect faces that exist in the image and trying to locate each face in a previously ...
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ژورنال
عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2020
ISSN: 2502-4760,2502-4752
DOI: 10.11591/ijeecs.v20.i3.pp1513-1521