1. Firstly, an entropy based feature detector is used to select regions of interest in the image. Once the regions of interest are obtained (which are of varying scales ‘scale’ being the radius of the circular region of interest), each circular feature is mapped to a square of size 11 by 11. Thus, the feature-extractor ends up with 121-dimensional features. The goal is to build proper probabili...

The first step in an automatic face recognition system is to localize the face region in a cluttered background and carefully segment the face from each frame of a video sequence. In this paper, we propose a fast and efficient algorithm for segmenting a face suitable for recognition from a video sequence. The cluttered background is first subtracted from each frame, in the foreground regions, a...

Real time faces detection and face tracking is one of the challenging problems in application like computer human interaction, video surveillance, biometrics etc. In this paper we are presenting an algorithm for real time face detection and tracking using skin color segmentation and region properties. First segmentation of skin regions from an image is done by using different color models. Skin...

This paper presents an approach to recognize human facial expressions for human-robot interaction. For this, the facial features, especially eyes and lip are extracted and approximated using Bézier curves representing the relationship between the motion of features and changes of expressions. For face detection, color segmentation based on the novel idea of fuzzy classification has been employe...

Introduction and General Characteristics: The fan-shaped deposits of the Tharsis Montes generally share three major facies: 1) Ridged facies, 2) Knobby facies, and 3) Smooth facies. The ridged facies consists of narrow, parallel, concentric ridges interspersed in places with small hills [1]. The hummocky or knobby facies consists of dense concentrations of small sub-km scale circular to irregul...

With man One of the most critical tasks in automated face recognition technology is the extraction of facial features from a facial images. The most critical task in each face recognition (FR) technology, which contributes the most to the success of particular FR products in particular applications and which is highly protected by industries developing those products, is the extraction of facia...

<p><span lang="EN-US">Face recognition technology has been used in many ways, such as the authentication and identification process. The object raised is a piece of face image that does not have complete facial information (occluded face), it can be due to acquisition from different point view or shooting angle. This was because affect detection performance whole. Deep leaning metho...

IN these days of modern diagnosis and free treatment, gummatous ulceration of a severe type is relatively rarely encountered in persons under the age of forty-five years. It is seen, as a rule, in elderly people whose primary infection dates back for many years. The patient concerned here is a married woman, thirty-four years of age and under 8 stone in weight. She first attended at Salford Mun...

Real-time face detection technology can be applied in many industrial or commercial products. Many face detection applications use the traditional Adaboost face detection system which is proposed by Viola and Jones in 2004. Viola and Jones used the Adaboost training algorithm and the Haar-like features in their proposed traditional Adaboost face detection system, which has a high detection rate...