A Flexible Sub-Block in Region Based Image Retrieval Based on Transition Region

Abstract

One of the techniques in region based image retrieval (RBIR) is comparing the global feature of an entire image and the local feature of image’s sub-block in query and database image. The determined sub-block must be able to detect an object with varying sizes and locations. So the sub-block with flexible size and location is needed. We propose a new method for local feature extraction by determining the flexible size and location of sub-block based on the transition region in region based image retrieval. Global features of both query and database image are extracted using invariant moment. Local features in database and query image are extracted using hue, saturation, and value (HSV) histogram and local binary patterns (LBP). There are several steps to extract the local feature of sub-block in the query image. First, preprocessing is conducted to get the transition region, then the flexible sub-block is determined based on the transition region. Afterward, the local feature of sub-block is extracted. The result of this application is the retrieved images ordered by the most similar to the query image. The local feature extraction with the proposed method is effective for image retrieval with precision and recall value are 57%.

Content Based Image Retrieval Busana Muslimah Menggunakan Fitur Kombinasi PHOG dan DCD

“…Citra Dataset merupakan kumpulan citra. Adapun fitur-fitur yang dapat digunakan yaitu fitur tekstur , warna, dan bentuk [7]. CBIR berjalan pada dua sisi yaitu sisi query (citra query) dan sisi basis data (citra dataset) dengan tahapan proses yaitu preprocessing, ekstraksi fitur, dan pencocokan fitur dengan menghitung jarak euclidean [8].…”

Median Filter For Transition Region Refinement In Image Segmentation

“…Transition region has three characteristics: transition region usually has a width of several pixels near the edge, it surrounds the object and should lie between the object and the background, there is a grey level change in the pixels in the transition region. Information for transition region extraction can be obtained from transitional pixels that have larger size and frequency of grey level changes than non-transitional pixels [19]. The transition region extraction process aims to obtain a transition zone close to the outline of the object [14].…”