A Comparative Analysis of Different Time Bounded Segmentation Techniques
Tanya Makkar, Yogesh Yogesh, Adityan Jothi · 2018 International Conference on Computing, Power and Communication Technologies (GUCON) · 2018
Images are considered to be one of the best tools for analyzing and visualizing the information for various fields of research. Thus, for interpreting images and to obtain features extraction, image segmentation technique is regarded as a prior step to be used. Image segmentation involves segregating images into various sections containing pixels that share similar information. Many applications based segmentation approaches have been proposed like-Thresholding technique, Edge detection, Watershed segmentation etc. that are involved in the analysis of image accurately. So, a novel method has been implied in this paper, depicting the use of the segmentation technique. In this paper, comparison of the proposed algorithm is done with the three-segmentation algorithm taken in response- Thresholding technique, Canny Edge Detection and Hough Transformation. The analysis is done by examining the time factor of all algorithms. The study counts the time consumed by each algorithm and the proposed method leading to a contrast producing the best algorithm with less time consumed. Several segmentation methodologies have been proposed since the inception of this field, each having its own advantages and disadvantages. The results portray an agreeable execution of this approach and hence considered to be a flexible and robust technique by intuitive usage.