Faces and Facial Features Detection in Color Images

Abstract

Human face detection is concerned with finding the location and size of every human face in a given image. Face detection plays a very important role in human computer interaction field. It represents the first step in a fully automatic face re cognition, facial features detection, and expression recognition. There are many techniques used in face detection, each one has its advantages and disadvantages. The face detection system presented in this paper is a hybrid of known algorithms. First stag e of the proposed method is applying skin detection algorithm to specify all skin locations in the image. Second, extract face features like eyes, mouth and nose. At the last, a verification step is applied to ensure that the extracted features are facial features. In experiments on images having upright frontal faces with any background our system has achieved high detection rates and low false positives.

A novel finger and hand pose estimation technique for real-time hand gesture recognition

“…Many geometrical characteristics can be used to detect hand existence in image sequences via projection, such as contour, fingertip and finger orientation [26]. Other non-geometrical features, i.e., color [2], strip [34] and motion can also be used for hand detection. Due to the complex background, unpredictable environmental factors and diversified hand shapes, hand gesture segmentation is still an open issue.…”

A general review of human face detection including a study of neural networks and Haar feature-based cascade classifier in face detection

“…Moreover, in recent years a lot of pattern recognition and heuristic based methods have been proposed for detecting human face in images and videos [2]. Face detection is the first stage of many face processing systems, including face recognition, automatic focusing on cameras, automatic face confusion in pictures, pedestrian and driver drowsiness detection in cars, criminal identification, access control, etc [3]. The challenging issue which can be mentioned in face detection is inherent diversity in faces such as shape, texture, colour, got a beard\moustache and/or glasses.…”

Face Detection using Color based Segmentation and Edge Detection

“…Face detection rate and the number of false positives are important factors in evaluating face detection systems. Face detection rate is the ratio between the number of faces correctly detected by the system and the actual number of faces in the image [5] [6]. Most face detection systems attempt to extract a fraction of the full face, thereby eliminating most of the background and other areas of an individual's head such as hair that are not necessary for the face recognition task [7].…”