Copyright: © the author(s), publisher and licensee Technoscience Academy. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited International Journal of Scientific Research in Computer Science, Engineering and Information Technology ISSN : 2456-3307 (www.ijsrcseit.com) doi : https://doi.org/10.32628/CSEIT1228139 222 Comparison of Segmentation-Based Image Compression Using Threshold, Region Growing, and Edge Detection Soumya Chaturvedi 1 , Dr. Pallavi Khatri 2 1 M. Tech, Department of Computer Science, ITM University, Gwalior, Madhya Pradesh, India 2 Professor, Department of Computer Science, ITM University, Gwalior, Madhya Pradesh, India Article Info Volume 8, Issue 1 Page Number : 222-228 Publication Issue : January-February-2022 Article History Accepted : 05 Feb 2022 Published :17 Feb 2022 ABSTRACT In the presenting paper we are dealing with to develop a lossless image compression (IC) method to utilize spatial redundancies inbuilt in image data which employs a best possible amount of segmentation information. To obtaining Multiscale segmentation we are using a earlier proposed transform which gives a tree-structured segmentation of the picture into regions which are identified by grayscale homogeneity. In the given proposed algor we have to shorten the tree to controlling the size and no of regions so that we can get a rate balance between the derived the coding gain and the operating cost inherent in coding the segmented data. Another uniqueness of the given proposed approach is that we are using an image model contain individual descriptions of the pixels lying close to the edges of a section and others lying in the center. In our results we can see that this proposed algorithm is providing better performance comparable to all the best available methods and it provides 15-20% better compression if we compare it with the JPEG lossless image compression standard for a enormous variety of images. Keywords : Digital Image Compression Technique, Digital Image Segmentation, JPEG Edge Detection Technique , Threshold Algorithms etc. I. INTRODUCTION In digital Image compression, by word ‘compression’ we mean the matter of to lessen the total sum of data we need for representing a digital image (DI). it's a technique which actually implied that how to create a minimal outline of a photograph, in this way reducing capacity the picture transmission necessities transmission prerequisites. Each picture can have extra information. Repetition denotes that the duplicity of accessible data inside the picture. Either it will revise segment in that picture or a specific example that is revised all the time in the picture. By fascinating advantage of redundant info of available image, compression occurs. Lessening of redundancy give helps to accomplish a reduction of space for storage of a picture. Compression is completed when at least one from those present redundancies are dispensed with. In idea of pressure, essentially three data redundancies are known and distorted. Pressure