In case of intelligent biometric system facial features identification is a challenging task. Facial features like eye, mouth, lip are the critical factor to express human emotion. Face and facial features detection can be implemented automatically with the help of computer, but it is difficult work. In this paper we have proposed a new frame work for a fast and efficient detection of face and facial features like eyes, nose, mouth and lip from the color images. Here the face image is give as input and facial features like eyes, mouth and lip are given as output. The performance of our algorithm is developed by the skin color segmentation and it is based on three stages, face detection, region localization and facial features detection. Our proposed algorithm is modified from RGB and HSV color space, which give better performance. Our experimental result show the proposed algorithm is better to detect the facial features than viola and jones based on statistic method. It reduces the position of image, expression, illumination variation problem. The average accuracy of our algorithm is 97.69% and easy to extract the facial features from the color images.
Keywords-face detection; region localization; skin colour segmentation; eye detection; lip detection.
I. INTRODUCTION
Face and facial features extraction is one of the most challenging problems in disciplines such as image processing, pattern recognize and computer vision. Because of various pose, facial expression, orientation, light condition, color of images. With the improvement of information technology facial features identification has wide usage in the application, such as personal identification, video surveillance, AVSR (audio visual speech recognize), witness face ...
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...C, LHS, RGB (red, green, blue) and modified RGB etc. In this paper we are introduced a pixel based skin color detection method because it is faster than other method. It can classify every pixel as skin or non skin from its neighbors. By this method we first detect the face from the image. The YCbCr color space [10] [16] is used for the skin color segmentation of the facial features. Eyes and mouth regions are extracted from the face image. Facial region around the regions are eliminated by applying threshold value. After the facial region elimination facial features are detected from the whole images by color segmentation but it has small unwanted pixels, which are reduced by image erosion and image dilation through morphological process. Now image is converting to binary image and connects the existing components to detect facial features like eyes, mouth and lip.
Biometrics-based authentication applications include workstation, network, and domain access, single sign-on, application logon, data protection, remote access to resources, transaction security and Web security (Campbell, 1995). Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital signatures, biometrics are set to pervade nearly all aspects of the economy and our daily lives (Campbell, 1995). Among the features measured are; face, fingerprints, hand geometry, iris, and voice (Campbell, 1995).
Color is widely remarked as one of the most demonstrative visual features, and as such it has been largely studied in the context of CBIR, thus number one to a rich variety of descriptors. As traditional color features used in CBIR, there are color histogram, color correlogram, and dominant color descriptor (DCD) [1,3,4]. A simple color similarity between two images can be
Biometric verification performs comparison of biometric template with the one it has on records. Face recognition is one of the techniques used in biometric verification. While performing face recognition on mobile platform it does not only suffer
The term biometrics is commonly known as the field of development of statistical and mathematical methods applicable to data analysis problems in the biological sciences. Though, even more recently it has taken on a whole new definition. Biometrics is an amazing new topic referring to “the emerging field of technology devoted to the identification of individuals using biological traits, based on retinal or iris scanning, fingerprints, or face recognition”. Biometrics has already begun using applications that range from attendance tracking with a time clock to security checkpoints with a large volume of people. The growing field of biometrics has really been put on the map by two things, the technological advances made within the last 20 years, and the growing risk of security and terrorism among people all over the world. In this paper I will focus on: the growing field of biometrics, why it is important to our future, how the United States government has played a role in its development and use, the risks involved, the implications on public privacy, and further recommendations received from all over the science and technology field.
A biometric recognition system can be used with a number of physiological characteristics (e.g. fingerprint, palmprint, hand geometry, face, iris, ear shape, and retina vein) and behavioral characteristics (e.g. gait, voice, signature and keystroke dynamics) to provide automatic identification of individuals based on their inherent physical and /or behavioral characteristics. Among these biometrics, iris recognition is one of the most accurate and reliable biometric for identification because of following characteristics (i) Iris pattern has complex and distinctive pattern such as arching ligaments, crypts, corona, freckles, furrows, ridges, rings and a zigzag collarette [1]. (ii) possess 266 degrees-of-freedom in variability and uniqueness in the order of one in 1072 [2].
Biometrics is described as the use of human physical features to verify identity and has been in use since the beginning of recorded history. Only recently, biometrics has been used in today’s high-tech society for the prevention of identity theft. In this paper, we will be understanding biometrics, exploring the history of biometrics, examples of today’s current technology and where biometrics are expected to go in the future.
I’m going to start off by stating that facial recognition has some benefits to offer for both businesses and consumers. Up until the last couple of years, this technology has been generally used by law enforcement to stop known criminals and for border control, but since then companies have shown more interest in using it for commercial uses. Companies
Feature extraction on the basis of principle lines: Any palm print have several principal lines in it, on the basis of these feature extraction is quiet useful for recognition and extraction of palm print recognition system.
[8] The Colour Image Processing Handbook By Sangwine, Stephen J.; Horne, Robin E.N. (Eds.)1998, XV, 440 p
[6] Rala M. Ebied,” Feature Extraction using PCA and Kernel-PCA for Face Recognition”, in The 8th International Conference on INFOrmatics and Systems Computational Intelligence and Multimedia Computing Track , 2012 ,pp mm72-mm77
Biometric technology is used for the ways humans can be identified by unique aspects of their bodies, such as fingerprints, body odor, our voices and many more. If one was to think about privacy rights, he/she would be concerned about the widespread adoption of these systems, since such systems could easily be used to develop a record of known rebellious people and/or dangerous criminals, to be used for social control purposes. Although that may seem pretty good and a positive thing for the society, one should take into account of the defects and errors of technology. Of the many biometrics technologies that are being developed and are already developed, facial recognition is one of the most threatening because it can be deployed secretly; one may not know whether or when they can be caught in a surveillance camera for such facial recognition biometrics. Additionally, tests have found that the miscalculations for facial biometrics technologies are very high. As a result, according to Privacy Rights Clearinghouse, innocent people can be erroneously identified as dangerous criminals and actual dangerous criminals and/or suspected terrorists can fail to be detected overall, allowing for a huge injustice and unfairness. Privacy rights concerned with biometrics have sparked a concern and should be dealt with; otherwise, this is just one of the
Since the entire image frame will not contain the same size of face, so skin detection will be applied in order to decrease the calculation time in finding the face. The skin colour will become as a requirements for human face presence. In such a way that we will eliminate those non-skin colour region to limit the search range in the face detection process, so the speed in finding face can be increased.
They also found that region based methods are also time consuming and not give effective segmentation. They proposed a new region based method based on Least Square method in order to detect objects sharply. They used a weight matrix for region based method which also takes the local information into account and also the usage of Least Square method provides optimal and fast segmentation. Comparison of their method is conducted with Otsu method and Chan-Vese method using Lena image. Their method can extract the features more accurately than other methods.
There must be some solid personal recognition schemes for a wide variety of system either to determine or conform the identity of the people who do services. The purpose is that to ensure the provided services are accessed only by the user and no other people can do so. Some of the examples of such process includes secure access to computers, laptops, buildings, security places etc. In absence of these schemes these systems are vulnerable to misuse. Therefore biometrics is introduced which refers to a secured access of an individual by automatic recognition based upon their behavioral and physiological characteristics. Using Biometrics we can conform an individual’s identity based on “who he is” rather than “what he has”. This paper gives a brief view of Biometrics, its advantages and disadvantages, the advancement of biometrics in now a days security management.
Iris recognition is very accurate and distinctive because iris has a complex texture that can produce a substantial amount of information to identify a person. Furthermore, the iris remains almost unchanged from childhood, only minuscule variations are presented. The biometric data is captured using a small and high definition camera that is able to recognize different characteristics of the iris. Moreover, the system can detect the use of contact lens with a fake iris and can realize with the natural movement of the eye if the sample object is a living being. Although initially iris recognition systems were expensive and complex to use, new technology developments have improved these weaknesses.