A Brief Review of Optimization of Methods for Image Segmentation by using Thresholding Techniques
Neha Singh Baghel · International Journal for Research in Applied Science and Engineering Technology · 2020
Image segmentation is important part of computer vision and image processing. The applicability and diversity of image segmentation are increase day to day in various engineering and scientific filed for the purpose of data analysis and prediction of particular object in given image [10]. For the processing of image segmentation various technique are used some technique are based on histogram of image and some technique are based on image content such as color, texture and shape & size. In mid-decade used the concept of threshold based image segmentation technique. Threshold based image segmentation technique overcomes the limitation of pervious method of image segmentation. The threshold based image segmentation method performs in terms of local, global and adaptive image segmentation techniques. The process of local and global image segmentation technique differs only in the selection of parameter for the threshold. The selection of threshold value includes the process of image binarization. The local and global image segmentation technique is based on the method of iteration [11]. The process of image iteration cannot be always good for image similarity index for segmented area. In this dissertation the analysis of image segmentation technique is performed based on thresholding technique. For the evaluation of the algorithm performance execution time is used. For the validation of local and global algorithm some standard image dataset is used such as boat, cameraman and Barbara.