Mahmoud Hassaballah

Learn More
Automatic detection of facial features plays an important role in many face-related applications. Among these features, nose region is the least varying part of the human face. In this paper, a method for nose region detection is presented. The method adopt Independent Components Analysis (ICA) as a subspace classifier to classify the face candidate region(More)
Fractal image compression gives some desirable properties like resolution independence, fast decoding, and very competitive rate-distortion curves. But still suffers from a (sometimes very) high encoding time, depending on the approach being used. This paper presents a method to reduce the encoding time of this technique by reducing the size of the domain(More)
Eyes are the most salient and stable features in the human face, and hence automatic extraction or detection of eyes is often considered as the most important step in many applications, such as face identification and recognition. This paper presents a method for eye detection of still grayscale images. The method is based on two facts: eye regions exhibit(More)
BACKGROUND AND STUDY AIMS The azygos vein plays an important role as a drainage system for the superior portosystemic collateral circulation in portal hypertensive patients. Endoscopic ultrasonography (EUS) and Doppler EUS allow the performance of hemodynamic studies of the azygos vein. In this study, we observed the changes in the azygos vein which occur(More)
Face detection is a fundamental research area in computer vision field. Most of the face-related applications such as face recognition and face tracking assume that the face region is perfectly detected. To adopt a certain face detection algorithm in these applications, evaluation of its performance is needed. Unfortunately, it is difficult to evaluate the(More)
Detection of facial features such as eye, nose, and mouth is an important step for many subsequent facial image analysis tasks such as face recognition. In this paper, we introduce a method to detect eye and nose fields from gray scale facial images. The Independent Components Analysis (ICA) is utilized to learn the appearance and shape of the facial(More)
Face detection is one of the most important areas of research in computer vision due to its various uses in a wide range of human face-related applications. This paper proposes a method for detecting faces in uncontrolled imaging conditions using a probabilistic framework based on Hough forests. Hough forests can be regarded as task-adapted codebooks of(More)