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2 Abd Allah M. M.

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ANN Face Detection with Skin Color Distribution Rules

Abd Allah M. M.

Machine Graphics and Vision

2011

Vol. 20, No. 1

93-108

This paper develops a face detection method in color images using a multi-layer Neural Network classification. The proposed method is based on two image processing steps which first detect skin regions in the color image and then extract face information from those regions. Instead of performing huge search in every part of the test images, a pre-processing method for candidate face regions guides the image search using neural networks. The new algorithms perform fast and accurate face detection. Experiments have been carried out and satisfactory results have been obtained which indicate the robustness of the first process to detect faces under different environmental conditions.

A novel approach for fingerprint classification system based on new feature area search

Abd Allah M. M.

Machine Graphics and Vision

2005

Vol. 14, No. 2

201-212

The paper presents a new fast fingerprint classification method based on direction patterns. The method is designed to be applicable to today's embedded systems for fingerprint authentication, in which small area sensors are employed (large enough to capture all the core and delta points of a fingerprint). The proposed procedure consists of four steps. First, ridge direction is determined at the pixel level. Second, average orientation field flow is assessed within 8x8 blocks. Then pattern matching is applied to determine presence of either of three "feature areas". Finally, the target classes are identified through a novel classification approach, called generally a pattern area. We prove that the search of direction pattern in a specific area is able to classify fingerprints clearly and quickly. With our algorithm, the classification accuracy of 94% is achieved over 4000 images in the NIST-4 database, slightly lower than the conventional approaches. However, the classification speed has improved tremendously, up to about 10 times faster than the conventional singular point approaches at the pixel level.