An Image Enhancement Technique for Poor Illumination Face Images
Face recognition is used to identify one or more persons from still images or a video image sequence of a scene by comparing input images with faces stored in a database. The face images used for matching the image in the database has to be of good qualit
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Abstract Face recognition is used to identify one or more persons from still images or a video image sequence of a scene by comparing input images with faces stored in a database. The face images used for matching the image in the database has to be of good quality with normal lighting condition and contrast. However, face images of poor illumination or low contrast could not be recognized properly. The objective of the work is to enhance the facial features eyes, nose, and mouth for poor contrast facial images for face recognition. The image enhancement is done by first detecting the face part, then applying contrast-limited adaptive histogram equalization technique and thresholding to enhance the facial features. The brightness of the facial features is enhanced by using logarithm transformation. The proposed image enhancement method is implemented on AR database, and the face images appear visually good when compared to original image. The effectiveness of the enhancement method is compared by analyzing the histogram. Keywords Image enhancement Face images Histogram
Facial features Illumination
1 Introduction Image processing techniques are used in various fields such as automated inspection of industrial parts and security systems, automated biometrics, i.e., iris recognition, fingerprint features and authentication, face recognition. There is a growing interest in biometric authentication, for use in application areas such as National ID cards, airport security, surveillance, site access. A wide variety of biometrics, such as A. Thamizharasi (&) Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, India e-mail: [email protected] J.S. Jayasudha SCT College of Engineering, Pappanamcode, Trivandrum, Kerala, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2018 M.S. Reddy et al. (eds.), International Proceedings on Advances in Soft Computing, Intelligent Systems and Applications, Advances in Intelligent Systems and Computing 628, https://doi.org/10.1007/978-981-10-5272-9_16
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A. Thamizharasi and J.S. Jayasudha
automated recognition of fingerprints, hand shape, hand written signature, and voice, has been used. However, all of these systems need some cooperation from the operator. Face recognition and iris recognition are some of the noninvasive methods of identification of people. Faces are the most common way people recognize each other. According to many researchers, it is not very convenient for computers to recognize individuals using faces. This is because human beings and computers possess different talents. The computers look at the face as a map of pixels of different gray (or color) levels. In machine-based face recognition, a gallery of faces is first enrolled in the system and coded for subsequent searching. A probe face is then obtained and compared with each coded face in the gallery; recognition is noted when a suitable match occurs. The challenge of such a system is to perform recognition of the face despite transformations: changes
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