Query-Based Image Retrieval using Support Vector Machine (SVM)

In many industries, the picture of the day now plays an important role in extracting information about the item. Many traditional image retrieval techniques have been used. It answers the user's question interactively by asking whether the image is relevant. In this digital age, graphics have become an important part of information processing. The image plays an important role in extracting information about the object in a variety of areas, including weather systems, tourism, medicine, and geology, in the processing of image registrations. There are several methods for retrieving images. It determines a person's inquiry interactively by asking users whether the image is relevant (similar). The efficient image database business has improved the process's functioning in the content-based image recovery system (CBIR). Content-based image recovery (CBIR) research has grown in importance. As individuals, we have studied and investigated various features in this manner or in combinations. We discovered that image Registration Processing (IRP) is a critical area in the industries. Several research papers on color feature and texture feature extraction were reviewed, and it was determined that point cloud data structure is best for image registration using the Iterative Closest Point (ICP) algorithm.