Illumination and contrast correction strategy using bilateral filtering and binarization comparison

Abstract

Illumination normalization and contrast variation on images areone of themost challenging tasks in the imageprocessing field. Normally, the degrade contrast imagesarecaused by pose, occlusion, illumination,and luminosity. In this paper, a new contrast and luminosity correction technique is developed based on bilateral filtering and superimpose techniques. Background pixels was used in order to estimate the normalized background using their local mean and standard deviation. An experiment has been conducted on few badly illuminated images and document images which involve illumination and contrast problem. The resultswereevaluated based on Signal Noise Ratio (SNR) and Misclassification Error (ME). The performance of the proposed method based on SNR and ME wasvery encouraging. The results also show that the proposed methodis more effective in normalizing the illumination and contrastcomparedtoother illumination techniques such as homomorphic filtering, high pass filter and double mean filtering (DMV).