An improved local binary pattern based edge detection algorithm for noisy images

Local Binary Pattern (LBP) is considered as an effective image descriptor as it is based on joint distribution of gray level differences. The main attributes of LBP are discriminatory power, robustness to brilliance change, simplicity and computational efficiency. In contrary LBP is highly sensitive to noise, rotation, non-rigid deformation, view point variations and scaling. Therefore, in the present work an improved version of LBP i.e. ILBP is proposed to overcome the limitations of basic LBP. ILBP replaces the fixed-weighted matrix of basic LBP by a pixel difference matrix. The proposed method is assessed on synthetic as well as real-time images. The results obtained are compared with LBP and other state-of-the-art edge detection techniques like HLBP, Canny and Sobel methods. The results reveal that performance of ILBP is superior to other edge detection methods under consideration. Further the proposed technique is highly efficient for noisy, blurred and low pixel valued images.