Image Segmentation Using Machine Learning Domain: Machine Learning

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Dr. V. Biksham, Yanagandula Nandini, K. Prasanna Vaishnavi, Naredla Meghana, Palthavath Venkatesh, Vepachettu Abhilash

Abstract

Main aim of Image segmentation project is to extract important data from images. Using this extracted information description, interpretation and understanding of the scene can be provided by the machine. Main point of image segmentation is to modify images in to desired manner. This system allows users to take hard copy of the image using printer routines and provides option for users to store file in to disk in different formats. In other word’s image processing is called as altering and analysing pictorial information of images. In our daily life we come across different type of image processing best example of image processing in our daily life is our brain sensing lot of images when we see images with eyes and processing is done is very less time. In existing system there are many techniques which are available for extracting information from images but there are no exact processing is defined. In proposed system we will come across different new techniques in image processing. You would have probably heard about object detection and image localization. When there is a single object present in an image, we use image localization technique to draw a bounding box around that object. In the case of object detection, it provides labels along with the bounding boxes; hence we can predict the location as well as the class to which each object belongs. Image segmentation results in more granular information about the shape of an image and thus an extension of the concept of Object Detection.

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