Digital image processing algorithms
Digital image processing algorithms
Handbook of image processing operators
Handbook of image processing operators
Face Pose Discrimination Using Support Vector Machines (SVM)
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Pose Estimation for Central Catadioptric Systems: An Analytical Approach
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Fuzzy ARTMAP network with evolutionary learning
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
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In this paper we propose a method of locating face and eyes using context-aware binarization. Face detection obtains the face region using neural network and mosaic image representation. Eye location extracts the location of eyes from the detected face region. The proposed method is composed of binarization, connected region segmentation by labeling, eye candidate area extraction by heuristic rules that use geometric information, eye candidate pair detection, and eye area pair determining by ranking method. Binarization plays an important role in this system that converts a source image to a binary image suitable for locating eyes. We consider edge detection based and image segmentation based binarization methods. However, each method alone cannot be used a solution in general environment because these are influenced by the factors such as light direction, contrast, brightness, and spectral composition. We propose a hybrid binarization using the concept of illumination context–awareness that mixes two binarization methods in general environment.