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In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented. The algorithm is a modification of the Santos and Proenka Method. In the first step, we detect the face and the eyes using classifiers based on Haar-like features. We then segment out the sclera, from the detected eye region. From the segmented sclera, we segment out an approximate eyelid contour...
Estimating eye centers is an important computer vision problem with several applications. In the past, eye center localization was constrained by the use of special hardware such as infrared cameras. Methods that estimate eye centers based on visible light have also been suggested in the literature, but these methods are inaccurate when used with low resolution images and wide ranges of lighting....
The quality of images often is affected adversely by illumination and contrast,leading to the need for illumination compensation in image enhancement. The main objective of this paper is to describe how to correct the local contrast in different area of the image so that the invisible features in the dark and bright areas are brought out and made visible to the human eye. Considering the fact that...
This paper describes a face recognition algorithm that extracts the eyes, nostrils and mouth features from cumulative distribution function (CDF) by applying Otsu thresholding. The algorithm, which is inspired by the probability of white pixels of binary facial image, has been tested using the BioID frontal face large database in different illuminations, expressions and lighting conditions. Illumination...
Face segmentation is a first step for face biometric systems. In this paper we present a face segmentation algorithm for thermographic images. This algorithm is compared with the classic Viola and Jones algorithm used for visible images. Experimental results reveal that, when segmenting a multispectral (visible and thermal) face database, the proposed algorithm is more than 10 times faster, while...
Lip contour extraction is crucial to the success of a lipreading system. This paper presents a lip contour extraction algorithm using localized active contour model with the automatic selection of proper parameters. The proposed approach utilizes a minimum-bounding ellipse as the initial evolving curve to split the local neighborhoods into the local interior region and the local exterior region, respectively,...
This paper describes an illumination normalization technique which works at the pre-processing stage where the face image is first divided into equal sub-regions. Each sub-region is then processed separately for illumination normalization. Then the segments are joined back followed by further processing like noise removal and contrast enhancement. The proposed technique is tested on Yale dataset and...
Reliable personal recognition is critical to many government and business processes. Iris recognition technology has been successfully applied to person verification and identification. However, all commercial products require user cooperation for iris image capture. Over the last three years, the community have paid more attention on the process of iris images taken with less user cooperative. In...
Variable illumination conditions, especially the side lighting effects in face images, form a main obstacle in face recognition systems. To deal with this problem, this paper presents a novel adaptive region-based image preprocessing scheme that enhances face images and facilitates the illumination invariant face recognition task. The proposed method first segments an image into different regions...
In this paper, we introduce a novel face representation method for face recognition, called Local Line Binary Pattern (LLBP), which is motivated from Local Binary Pattern (LBP) due to it summarizes the local spacial structure of an image by thresholding the local window with binary weight and introduce the decimal number as a texture presentation. Moreover it consumes less computational cost. The...
Recognizing human faces in various lighting conditions is quite difficult for a surveillance system. The problem becomes more difficult if face images are taken in extremely high dynamic range scenes. Most of automatic face recognition systems assume the images are taken under well controlled illumination. The face segmentation as well as recognition problem is much simpler under such a constrained...
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