9/21/2023 0 Comments Picture extractor and deduplicator![]() ![]() In this paper, we present two novel image representation methods based on the histograms of triangles, which add spatial information to the inverted index of BoF representation. While the Bag of Features (BoF) representation is commonly used for image retrieval, it lacks spatial information. An image represents regions and objects that are in a spatial semantic relationship with respect to each other. Standard images are constructed by following the rule of thirds that divides an image into nine equal parts by placing objects or regions of interest at the intersecting lines of the grid. The compositional and content attributes of images carry information that enhances the performance of image retrieval. The results of this study are to discuss the framework for the use of existing techniques to see gap for improvement that can be done in subsequent studies. The methodology is implemented in five phases which are review paper, collecting data, compare data, find out strength and weaknesses and come out with innovative ideas. Therefore, this study was conducted to study the techniques that have been used previously for defined the suitable technique that can be used and help in images features extraction because features extraction is the most important part in NDID research, in order to allow the system to understand what requirements and unique structure for different images. The issue and problem in NDID related to detection and clustering the similar images. Various techniques are used to help manage, detect and clustering ND images contained in the database, but the problem is, how accurately detecting NDID in features extraction and this study are still ongoing and facing several issue and problems. The content inside the database is in high quantities. Research in NDID always related with the database either conventional or cloud computing. Near-duplicate images detection (NDID) is a different image but have similarity in scenery, object and content. ![]()
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