IMAGE PROCESSING TECHNIQUES FOR DENOISING, OBJECT IDENTIFICATION AND FEATURE EXTRACTION

Abstract

An artifact such as image has its importance in human’s activities to the extent that we hardly can do away with it in our daily lives. As important as this artifact is, several constraints may inhibit its usefulness. Some of these constraints are containment of noise (Which greatly degrade the clarity property of the image), Identification of objects in the image and extraction of features. In this paper, the denoising methods of Two Stages Image Denoising By Principal Component Analysis With Local Pixel Grouping(PCA - LPG) and Non Linear Filtering Algorithm For Underwater Images are considered, Also the object identification methods of SCALE-INVARIANT FEATURE TRANSFORM (SIFT) and SPEEDED UP ROBUST FEATURES (SURF) are considered. Furthermore, the feature extraction methods of thresholding and subtraction and template matching are also considered. The consideration of these aforementioned techniques made it possible to draw some conclusions, hence, making of recommendation of better techniques are made possible. Each recommendation made for each of the problem are also implemented in C# programming language with the help of an open source computer vision library EmguCV to visualize the output of the recommended techniques. Finally the result i.e the output of the implemetation are discussed.

General Terms, Image Denoising, Object Identification, Feature Extraction, Algorithms.