Beschreibung
Contrast variables and uneven illumination are considered one of the most challenging tasks in the image processing field. The bad contrast images commonly caused by occlusion, pose, illumination which is highly nonlinear. Thus, the segmentation process will be extremely complex and difficult. In this work, contrast and luminosity correction technique will be developed based on statistical formulation. The background pixels will be used in order to estimate the normalize background using the mean and standard deviation. This experimented was tested with a few badly illuminated images and document images which involve illumination and contrast problem. The result will be evaluated and analysis properly. The main impact of this study is to eliminate the illumination and normalize the contrast variation. In conclusions, the implementation of the proposed method produces an effective and efficient result for background correction.
Autorenporträt
Degree in Biomedical Electronic Engineering (2013) and PhD in Mechatronic Engineering (2017), Fast Track Program at University Malaysia Perlis, Malaysia. Registered on Board Engineer Malaysia (BEM) 2014.Published more than 10 academic articles.Now working as a senior lecturer at University Malaysia Perlis, Malaysia.
