Face Detection and Facial Feature Extraction Based on a fusion of Knowledge Based Method and Morphological Image Processing
Detecting human faces and extracting the facial features from an image is a challenging process. It is very difficult to locate faces in an image accurately. There are several variables that affect the performance of the detection methods, such as wearing glasses, skin color, gender, facial hair, and facial expressions etc. We propose an efficient method for locating a face region and extracting facial features based on the characteristics of eye regions. The method proposed in this paper is based on the assumption that the frontal face image is available. The face regions are detected from a pair of possible eye candidates. Then, the facial features are extracted from the detected face regions. Our method for detecting and extracting the facial features is divided into two stages. At first, the eye pairs are detected by testing all possible eye regions in an image. After detecting a pair of eye candidates, the distance between the eyes is used to find a possible face candidate. Next, the face is divided into different regions and facial features are extracted from these regions. The extracted features consist of the eye corners, the iris, the nostrils, and the mouth corners.
I. INTRODUCTION
Human face detection and face image analysis have become one of the most important research topics in the world of pattern recognition and computer vision. The eye is the most important feature in a human face. The facial feature detection techniques aim to extract specific features such as, pupil, corners of the eyes, nostrils, lip corners, etc. Major applications of face detection consist of topics such as, face recog...
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...detecting the dark regions in the image. Based on the detected pair of eye candidates, possible facial regions are located by means of the geometric relationship between various features. Detection of eyes, mouth and nose are done by estimating the probable region for each feature. Geometrical interpretation of location of facial features, used in the algorithms is described with pictorial representation. It is observed that, with the use of facial geometry, the accuracy of features (eyes, nose and mouth) detection is greatly improved. The proposed method for feature extraction is also found to be accurate in detecting all kinds of frontal images. In conclusion, this method can achieve a high performance in detecting human faces and extracting facial features.
The system was tested on 25 people, and was successful with 20 people, resulting in 80% accuracy (Fig.5).
Another weakness in the experimental design was that the reliability of the experiment was very low. As each test subject was only tested against each amount of prior exercise once, the impact of random errors is likely very large, which can be seen by the spread of the data on the graph. Although, this was attempted to be rectified by averaging the results of all four test subjects, it does not improve reliability too
The most predominant feature of the human face is eyes. When talking to a person our eyes meet there eyes; the way that people identify each other is through eyes; eyes even have the power to communicate on its own. Eliezer identified people buy there eyes and knew their emotions through their eyes. “Across the aisle, a beautiful women with dark hair and dreamy eyes. I had
This however is not always the case as many studies have failed to validate these systems, some revealing poor sensitivity, poor positive predictive value and low reproducibility (Gao et al 2007; Smith et al 2008; Subbe et al 2007; Jansen et al 2010).
Retinal vessel segmentation is important for the diagnosis of numerous eye diseases and plays an important role in automatic retinal disease screening systems. Automatic segmentation of retinal vessels and characterization of morphological attributes such as width, length, tortuosity, branching pattern and angle are utilized for the diagnosis of different cardiovascular and ophthalmologic diseases. Manual segmentation of retinal blood vessels is a long and tedious task which also requires training and skill. It is commonly accepted by the medical community that automatic quantification of retinal vessels is the first step in the development of a computer-assisted diagnostic system for ophthalmic disorders. A large number of algorithms for retinal vasculature segmentation have been proposed. The algorithms can be classified as pattern recognition techniques, matched filtering, vessel tracking, mathematical morphology, multiscale approaches, and model based approaches. The first paper on retinal blood vessel segmentation appeared in 1989 by Chaudhuri et al. [21]...
The usage of the iris technology is very fast. The capturing and the testing of the images is very fast, it must require some training. The glasses must be removed during the enrollment in the recognition system will ensure the best image will be captured without any reflections from the glasses or the lenses.
are blacked out and if the eyes of a person’s face are a major factor
A cube a total of 6 sides, when it is places on a surface only 5 of
Hirayama, T., Iwai, Y., & Yachida, M. (2007, May). Integration of facial position estimation and person identification for face authentication [Electronic Version]. Systems & Computers in Japan, 38(5), 43-58.
Signal detection theory is introduced by mathematicians and engineer in 1950 . It started to evolve from the developing electronics communication.
[Jain, 2004] Jain, A.K.;Ross, A.;Prabhakar, S.;"An introduction to biometric recognition", Volume: 14 Issue: 1 Issue Date: Jan. 2004, on page(s): 4 - 20
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The concept of “beauty” is something that everyone feels, thinks, or wants, in order to fit society’s standards. In today’s society, we are often faced with the unrealistic ideals of what beauty is. Due to society’s constant portraying of unrealistic beauty ideals, this reinforces a negative influence upon women’s idea of beauty, resulting in a negative impact in their confidence, and self-esteem, which leads to others, specifically women to be manipulated by society’s corrupted outlook of what beauty is. To add onto this issue, we are constantly surrounded by sources of this negative influence in our everyday lives, including magazines, television, advertisements, and so on. However, women specifically, are more prone to be victims of this negative effect, thus will have more pressure upon themselves to match society’s idea of “beauty,” which includes unrealistic and sometimes unattainable beauty standards. Women especially, can sometimes be so deeply manipulated by society’s unrealistic ideals of what is beautiful, such that it’s possible that they don’t even realize it Furthermore, in order to do so, women often will receive negative impacts rather than positive impacts, such as in their confidence and self-esteem. The negative effects of society’s beauty ideals also lead women to have an overall corrupted idea of what is “beautiful.” Society creates unrealistic ideals of beauty towards women through the media by creating an unrealistic image of what women should look like to be considered beautiful. Men negatively affect women’s idea of beauty by using the unrealistic beauty standards exposed by society which further pressures women to try to fit society’s idea of what is beautiful. Beauty pageants negatively affect women’s ov...