To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Automatic human face detection is considered as the initial process of any fully automatic system that analyzes the information contained in human faces (e.g., identity, gender, expression, age, race and pose). In this paper, color segmentation is used as a first step in the human face detection process followed by grouping likely face regions into clusters of connected pixels. Median filtering is then performed to eliminate the small clusters and the resulting blobs are matched against a face pattern (ellipse) subjected to constraints for rejecting non-face blobs. The system was implemented and validated for images with different formats, sizes, number of people, and complexity of the image background. The results obtained were very satisfactory in terms of face identification and performance.
Keywords: Face detection, color segmentation, face pattern (ellipse)
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