Simultaneous Image Segmentation and Object Recognition
Gaurav Bansal · 2018
We have introduced the method to recognize the object in any given image. An object is an identifiable portion of image that can be treated as a single unit. For object recognition, we have used the method of blob detection algorithm. We have consider the assumption that the objects that are present in any image can be differentiated by using the object's property of size, shape and intensity. In this way, any desired object in the image can be easily identified, recognized and separated from the remaining portion of the image. Blob detection methods are specially designed to find regions in an image that differs in properties such as brightness, size or color as compared to surrounding regions. A blob is that region or part of the image which consists of almost constant properties, though we consider all the pixels present in a particular blob to be same. As only one characteristic of the object is not completely reliable to identify the type of object contained in the image, we will use as many properties of the object which would help us to differentiate between the objects as much as possible.