@article{(Open Science Index):https://publications.waset.org/pdf/12187, title = {A New Face Detection Technique using 2D DCT and Self Organizing Feature Map }, author = {Abdallah S. Abdallah and A. Lynn Abbott and Mohamad Abou El-Nasr}, country = {}, institution = {}, abstract = {This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.}, journal = {International Journal of Computer and Information Engineering}, volume = {1}, number = {3}, year = {2007}, pages = {489 - 493}, ee = {https://publications.waset.org/pdf/12187}, url = {https://publications.waset.org/vol/3}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 3, 2007}, }