In modern multimedia systems, video and image signals usually need to be indexed or retrieved according to their contents. Colour characteristics are proposed for use in detection of human faces in colour images with complex backgrounds. The proposed face detection method first uses a neural network to classify the images and then segments the candidate face regions. Then, an energy thresholding method which can take the shape, colour and edge characteristics of the face features into the extraction process is devised to extract the lips. Finally, three shape descriptors of the lip feature are used to further verify the existence of the face in the candidate face regions. The experimental results show that this method can detect faces in the images from different sources in an accurate and efficient manner. Since faces are common elements in video and image signals, the proposed face detection method is an advance towards the goal of content-based video and image indexing and retrieval.
Detection of human faces in colour images
1997-12-01
5 pages
Article (Journal)
English
neural network , image classification , colour characteristics , edge detection , shape descriptors , image indexing , candidate face regions , multimedia systems , human faces detection , shape characteristics , neural nets , complex backgrounds , colour images , energy thresholding method , image segmentation , image signals , video signals , feature extraction , edge characteristics , content-based video , image retrieval , image colour analysis , face features extraction , lip feature
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