Region Based Image Retrieval Using Ratio of Proportional Overlapping Object

• Published in: Telkomnika Vol. 14; no. 4; p. 1608
• Main Authors: Arifin, Agus Zainal, Sholikah, Rizka Wakhidatus, H. P., Dimas Fanny, Navastara, Dini Adni
• Format: Journal Article
• Language: English
• Published: Yogyakarta Ahmad Dahlan University 01.12.2016
• Subjects: Annotations; Feature extraction; Image management; Queries; Retrieval
• ISSN: 1693-6930; 2302-9293
• DOI: 10.12928/telkomnika.v14i4.4289

[...]in this study we proposed a system of RBIR based on the percentage of proportional objects that overlap with sub-blocks. Experimental results show that the proposed method has average precision with 74%. Introduction In the last few decades, Content Based Image Retrieval (CBIR) has become popular research. Searching images using their content has many advantages than using their annotation text, because not every images have annotation and not every annotations can resemble the images well. [...]CBIR is able to overcome the weakness of text-based image retrieval method. Local feature extraction from query image based on region is known as Region Based Image Retrieval (RBIR). Not every region is relevant to determine the user interest. [...]users have to define the Region of Interest (ROI) in image query so that the irrelevant region can be eliminated. [...]it is necessary to have a method that can be adapted well in the different size of object. Determine Proportional Overlapping Sub-blocks To determine the region as the query, image query is divided into fixed size n x n. In this paper we use 3 x 3 as shown in Figure 4. In this study, the determination of the weight parameter for each feature has an impact on the value of precision of the search results. Content based image retrieval based on relative locations of multiple regions of interest using selective regions matching. Improving Relevance Feedback in Image Retrieval by Incorporating Unlabelled Images.