{"title":"Face Detection Using Fusion of LBP and AdaBoost","authors":"Arezou Chehrehgosha, M. Emadi","doi":"10.5899/2016/JSCA-00064","DOIUrl":null,"url":null,"abstract":"The human face is a dynamic object which a high degree of variability exists in its appearance. This makes the face detection to be considered as the first and most essential step in face recognition systems. The aim of the face detection is the segmentation of the face. There are several problems in face detection, including state switching, changing light intensity, face covering, etc. To solve these problems, the present study utilizes an advanced algorithm based on the LBP method and a structured Adaboost algorithm using the FERET database. The output will be attained by entering the normalized data into a three-layer LBP Adaboost fed with the data from data bases. It was found that the method has the acceptable detection accuracy of 75%, detection feature of 72% and sensitivity of 77% , and the final detection result of the human face is up to 98% possible.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"20 1","pages":"1-10"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advances in Soft Computing and its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5899/2016/JSCA-00064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 5
Abstract
The human face is a dynamic object which a high degree of variability exists in its appearance. This makes the face detection to be considered as the first and most essential step in face recognition systems. The aim of the face detection is the segmentation of the face. There are several problems in face detection, including state switching, changing light intensity, face covering, etc. To solve these problems, the present study utilizes an advanced algorithm based on the LBP method and a structured Adaboost algorithm using the FERET database. The output will be attained by entering the normalized data into a three-layer LBP Adaboost fed with the data from data bases. It was found that the method has the acceptable detection accuracy of 75%, detection feature of 72% and sensitivity of 77% , and the final detection result of the human face is up to 98% possible.
期刊介绍：
The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.
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