Skin Segmentation based Elastic Bunch Graph Matching for efficient multiple Face Recognition
نویسنده
چکیده
This paper is aimed at developing and combining different algorithms for face detection and face recognition to generate an efficient mechanism that can detect and recognize the facial regions of input image. For the detection of face from complex region, skin segmentation isolates the face-like regions in a complex image and following operations of morphology and template matching rejects false matches to extract facial region. For the recognition of the face, the image database is now converted into a database of facial segments. Hence, implementing the technique of Elastic Bunch Graph matching (EBGM) after skin segmentation generates Face Bunch Graphs that acutely represents the features of an individual face enhances the quality of the training set. This increases the matching probability significantly.
منابع مشابه
A Face Recognition Method Based on Local Feature Analysis
Elastic Bunch Graph Matching has been proved effective for face recognition. But the recognition procedure needs large computation. Here we present an automatic face recognition method based on local feature analysis. The local features are firstly located by the face structure knowledge and gray level distribution information, rather than searching on the whole image as it does in Elastic Bunc...
متن کاملAverage Half Face Recognition by Elastic Bunch Graph Matching Based on Distance Measurement
Average-half-face experiments the overall accuracy of the system is better than using the original full face image. Clearly experiment shows that half face data produces higher recognition accuracy [5]. The average-half-face contain the data exactly half of the full face and thus results in storage and computational time saving. The information stored in average-half-face may be more discrimina...
متن کاملFace Recognition by Extending Elastic Bunch Graph Matching with Particle Swarm Optimization
Elastic Bunch Graph Matching is one of the well known methods proposed for face recognition. In this work, we propose several extensions to Elastic Bunch Graph Matching and its recent variant Landmark Model Matching. We used data from the FERET database for experimentations and to compare the proposed methods. We apply Particle Swarm Optimization to improve the face graph matching procedure in ...
متن کاملTwo Kinds of Statistics for Better Face Recognition
We briefly review the base techniques of elastic graph matching [1] and elastic bunch graph matching [2], which provide a method for face detection, matching, comparison, and identity decision. We then present a method that combines the advantages of Gabor-labeled graphs with maximum likelihood decision making. The improvements over pure bunch graph matching have been studied, and the method ha...
متن کاملFace Recognition by Eigenface and Elastic Bunch
The technology of face recognition has become mature within these few years. System, using the face recognition, has become true in real life. In this paper, we will have a comparative study of two most recently proposed methods for face recognition. One of the approach is eigenface and other one is the elastic bunch graph matching. After the implementation of the above two methods, we learn th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1310.6066 شماره
صفحات -
تاریخ انتشار 2012