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A biometric-based techniques emerge as the promising approach for most of the real-time applications including security systems, video surveillances, human-computer interaction and many more. Among all biométrie methods, face recognition offers more benefits as compared to others. Diagnosing human faces and localizing them in images or videos is the priori step of tracking and recognizing. But the...
A biometric-based techniques emerge as the promising approach for most of the real-time applications including security systems, video surveillances, human-computer interaction and many more. Among all biométrie methods, face recognition offers more benefits as compared to others. Diagnosing human faces and localizing them in images or videos is the priori step of tracking and recognizing. But the...
In this paper, a new algorithm is proposed for detecting human faces in color images and as well as for removing background from a single face color image. The proposed algorithm combines color histogram for skin color (in the HSV space), a threshold value of gray scale image to easily detect skin regions in a given image. Then, in order to reduce the number of non-face regions, we calculate the number...
This article deals with facial detection and tracking algorithm development. The most efficient method for facial monitoring, namely, template matching technique, was found by considering different tracking techniques. The authors enumerate main drawbacks of the template tracking and improve the algorithm according to the problem set. The following modifications to the template matching method were...
Computer vision plays an important role in problem solving, mainly in those problems which are focused on human monitoring, being the facial features the most important among them. In this paper, a methodology for detecting eyes and mouth via software is presented, using image processing techniques such as color space conversion, thresholding and erosion. It has the characteristic of being adaptable...
This article describes the algorithm for searching the human face by the camera. This device is placed in a robotic head. This head should be used for the submission of information when entering into a building such as e.g. a museum. It is therefore necessary for the head to react to the stimuli. If a person appears in front of the head, the head must look at the person and react to the person. The...
Face detection is necessary in many applications, like those for face recognition, face tracking in video sequences, gender classification, biometric identification, Human Computer Interaction systems, and others. There are many approaches to face detection. The majority of them use a window-based classifier, which detects human faces by translating a window on the entire image. This detection method...
Face detection is one of the important issues in Human Computer Interaction (HCI). In face detection, Local Binary Pattern (LBP) feature is popularly used because of its invariant for rotation and lighting condition. In this paper, we propose part-based face detection method using Skin-Color LBP (SLBP). The proposed feature SLBP shows better performance than LBP because it contains not only appearance...
Skin detection is one the most studied subjects in vision literature. Due to the appealing features of skin segmentation algorithms, they are widely used in different biometric applications such as face detection, face recognition, face tracking, hand gesture recognition, etc. However, several challenges such as nonlinear illumination, equipment effects, personal interferences, ethnicity variations,...
In this paper, a simple and fast algorithm was proposed to detect face. Firstly, some interest points marking skin regions were searched by only using simple chrominance Cr information instead of simultaneously using chrominance Cr and Cb. And then, a conventional and popular AdaBoost algorithm was employed to make a decision whether around the detected interest points was there face and then located...
This paper presents a hybrid method of iris detection system based on edge detection and Hough Transform, with the help of skin segmentation in face detection algorithm, Golden Face Ratio and geometric definition. The algorithm starts with skin detection using Gaussian mixture model to find the bounding area of the face. Next, the facial area is used to mask the area for eye segmentation process....
Skin detection plays a very essential role in many image processing applications such as face localization, face recognition, gesture recognition and human identification. A robust pre-processing skin detection algorithm can significantly increase the performance of an application in both terms of speed and accuracy. Skin segmentation is often computationally simple, though in many conditions, uneven...
Face detection is one of the most important parts of biometrics and face analysis science. Numerous methods and algorithms have been developed in recent years; however, there is a sensible gap between the current detection rate and the ideal one yet. In this paper, a novel multi-stage face detection method is proposed which can remarkably detect faces in different images with different illumination...
Face detection technology is a hot topic of pattern recognition and computer vision. The method based on skin color feature and AdaBoost are both the most representative methods. Among them, the former method has a faster detection speed, but lower accuracy; the latter method has a higher accuracy, but slower speed. In this paper, a fast face detection method based on the combination of skin color...
The customer analysis can be applied widely in many situations, such as surveillance system, digital signage, store entrance, etc. In digital signage application, when customers are viewing ads, the system can automatically analyze multiple attributes of customers, including customer's gender, age, height, viewing distance, the degree of interest and total number of visitors. The advertising companies...
For the original AdaBoost algorithm's long searching time, this paper improves the original face detection method which is based on AdaBoost face detection method using a simple rectangular features. The paper also proposes a method for rapid detection of human faces. First of all, we do HSV space transformation to the pretreatment of image, then add skin color segmentation to the image, and finally...
Face detection in video is a challenging and interesting topic, especially when it's applied in Automatic Teller Machine (ATM). We propose an efficient algorithm to detect arbitrary occluded faces in ATM surveillance. A novel and time-saving foreground extraction method is proposed to obtain accurate foreground. After that, we locate the face with two cascaded steps. An empirical rule-based face localization...
This work aims at designing a face detection system with high speed of processing and a reduced number of false positives compared to the well known Haar feature-based face detector developed by Viola and Jones. In this method, HS channels of HSV color space are logically combined for skin-color region extraction, then a blob-contour-property based filtering is used to indicate the optimum ROI (regions...
We have presented a fast wavelet transform based face detection algorithm. Firstly nonlinear transform has been done against image, then using wavelet transform extract facial high frenquency components. At the same time the hidden function of neural is repalced by wavelet kernel function. The result of experiment shows that the new algorithm can reduce the detection time and can get the high detection...
Improved face detection method based on information of skin colour and depth information is presented which is also able to differentiate between real face and picture face. This method can be apply to a service robot equipped with binocular camera system for real-time face detection and with this algorithm the service robot will able detect the real face instead of fake one. Hence the proposed algorithm...
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