Medical Image Contrast Enhancement via Wavelet Homomorphic Filtering Transform

A novel enhancement algorithm for magnetic resonance (MR) images based on spatial homomorphic filtering transform is proposed in this paper. By this method, the source image is decomposed into different sub-images by dyadic wavelet transform. Homomorphic filtering functions are applied in performing filtering of corresponding sub-band images to attenuate the low frequencies as well as amplify the high frequencies, and a linear adjustment is carried out on the low frequency of the highest level. Later, inverse dyadic wavelet transform is applied to reconstruct the object image. Experiment results on MR images illustrate that the proposed method can eliminate non-uniformity luminance distribution effectively, some subtle tissues can be improved effectually, and some weak sections have not been smoothed by the novel method.

Frequency and Spatial Domains Adaptive-based Enhancement Technique for Thermal Infrared Images

Low contrast and noisy image limits the amount of information conveyed to the user. With the proliferation of digital imagery and computer interface between man-and-machine, it is now viable to consider digital enhancement in the image before presenting it to the user, thus increasing the information throughput. With better contrast, target detection and discrimination can be improved. The paper presents a sequence of filtering operations in frequency and spatial domains to improve the quality of the thermal infrared (IR) images. Basically, two filters – homomorphic filter followed by adaptive Gaussian filter are applied to improve the quality of the thermal IR images. We have systematically evaluated the algorithm on a variety of images and carefully compared it with the techniques presented in the literature. We performed an evaluation of three filter banks such as homomorphic, Gaussian 5×5 and the proposed method, and we have seen that the proposed method yields optimal PSNR for all the thermal images. The results demonstrate that the proposed algorithm is efficient for enhancement of thermal IR images.Defence Science Journal, Vol. 64, No. 5, September 2014, pp.451-457, DOI:http://dx.doi.org/10.14429/dsj.64.687

Template based Mole Detection for Face Recognition

Face recognition is used for personal identification. The Template based Mole Detection for Face Recognition (TBMDFR) algorithm is proposed to verify authentication of a person by detection and validation of prominent moles present in the skin region of a face. Normalized Cross Correlation (NCC) matching, complement of Gaussian template and skin segmen tation is used to identify and validate mole by fixing predefined NCC threshold values. It is observed that the NCC values of TBMDFR are much higher compared to the existing algorithms

PCA-ANN Face Recognition System based on Photometric Normalization Techniques

The human face is the main focus of attention in social interaction, and is also the major key in conveying identity and emotion of a person. It has the appealing characteristic of not being intrusive as compared with other biometric techniques. The research works on face recognition started in the 1960s with the pioneering work of Bledsoe and Kanade, wh

Image Compensation Techniques.

Image clarity is very easily affected by lighting, weather, or equipment that has been used to capture the image

A Review: Image Compensation Techniques.

Image clarity is very easily affected by lighting, weather, or equipment that has been used to capture the image

Face Recognition Under Varying Illumination

This study is a result of a successful joint-venture with my adviser Prof. Dr. Muhittin Gökmen. I am thankful to him for his continuous assistance on preparing this project. Special thanks to the assistants of the Computer Vision Laboratory for their steady support and help in many topics related with the project