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- W2726866839 abstract "This paper introduces a novel technique to detect faces similarly recognizes in real-time with very high rate. It is essentially a feature-based approach, in which a classifier is trained for Haar-like rectangular features selected by Ada Boost algorithm and efficient representation method histogram equalization is used for varying illumination in the image. The face detection system generates an integral image window to perform a Haar feature classification during one clock cycle. And then it performs classification operations in parallel using Haar classifiers to detect a face in the image sequence. The classifiers in the beginning of the cascade are simpler and consist of smaller numbers of features. Although a face detection module is typically designed to deal with single images, its performance can be further improved if video stream is available.However, as one proceeds in the cascade, the classifiers become more complex. A region is reported as detection only if it passes all the classifier stages in the cascade. If it is rejected at any stage, it is discarded and not processed further. If all stages are passed the face of a candidate is concluded to be recognized face." @default.
- W2726866839 created "2017-07-14" @default.
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- W2726866839 date "2013-12-25" @default.
- W2726866839 modified "2023-09-23" @default.
- W2726866839 title "An Efficient Implementation Of Fpga Based Face Detection And Face Recognition System Using Haar Classifiers" @default.
- W2726866839 doi "https://doi.org/10.5281/zenodo.821745" @default.
- W2726866839 hasPublicationYear "2013" @default.
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