Slim-Tree and BitMatrix index structures in image retrieval system using MPEG-7 Descriptors

Date

2008-06-20

Author

Acar, Esra
Arslan, Serdar
Yazıcı, Adnan
KOYUNCU, Murat

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

31
views

0
downloads

Content-based retrieval of multimedia data has still been an active research area. The efficient retrieval in natural images has been proven a difficult task for content-based image retrieval systems. In this paper, we present a system that adapts two different index structures, namely Slim-Tree and BitMatrix, for efficient retrieval of images based on multidimensional low-level features such as color, texture and shape. These index structures also use metric space. We use MPEG-7 Descriptors extracted from images to represent these features and store them in a native XML database. The low-level features; Color Layout (CL), Dominant Color (DC), Edge Histogram (EH) and Region Shape (RS) are used in Slim-Tree and BitMatrix and aggregated by Ordered Weighted Averaging (OWA) method to find final similarity between any two objects. The experiments included in the paper are in the subject of index construction and update, query response time and retrieval effectiveness using ANMRR performance metric and precision/recall scores. The experimental results strengthen the case that uses BitMatrix along with Ordered Weighted Averaging method in content-based image retrieval systems.

Subject Keywords

Content-Based Image Retrieval, MPEG-7, Slim-Tree, Bitmatrix, OWA, XML Database

URI

https://hdl.handle.net/11511/40034

DOI

https://doi.org/10.1109/cbmi.2008.4564975

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Efficient index structures for video databases Açar, Esra; Yazıcı, Adnan; Department of Computer Engineering (2008) Content-based retrieval of multimedia data has been still an active research area. The efficient retrieval of video data is proven a difficult task for content-based video retrieval systems. In this thesis study, a Content-Based Video Retrieval (CBVR) system that adapts two different index structures, namely Slim-Tree and BitMatrix, for efficiently retrieving videos based on low-level features such as color, texture, shape and motion is presented. The system represents low-level features of video data with ...
Optical flow based video frame segmentation and segment classification Akpınar, Samet; Alpaslan, Ferda Nur; Department of Computer Engineering (2018) Video information retrieval is a field of multimedia research enabling us to extract desired semantic information from video data. In content-based video information retrieval, visual content obtained from video scenes is utilized. For developing methods to cope with content-based video information retrieval in terms of temporal concepts such as action, event, etc., representation of temporal information becomes critical. In this thesis, action detection is tackled based on a temporal video representation m...
A Study on particle filter based audio-visual face tracking on the AV16.3 dataset Yılmaz, Yunus Emre; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2016) People tracking has received considerable attention as a research field recently. Since, there are a wide range of application areas that requires to track single or multi target people in different environments with various scenarios using a variety of sensors. In this kind of tracking scenarios, usage of audio and visual information together is commonly preferred method, because these cues are mostly exist in the tracking environment and they contain complementary information about the targets. Our work f...
Text Generation and Comprehension for Objects in Images and Videos Anayurt Özyeğin, Hazan; Kalkan, Sinan; Department of Computer Engineering (2021-9-09) Text generation from visual data is a problem often studied using deep learning, having a wide range of applications. This thesis focuses on two different aspects of this problem by proposing both supervised and unsupervised methods to solve it. In the first part of the thesis, we work on referring expression comprehension and generation from videos. We specifically work with relational referring expressions which we define to be expressions that describe an object with respect to another object. For this, ...
Dominant sets based movie scene detection SAKARYA, Ufuk; Telatar, Ziya; Alatan, Abdullah Aydın (Elsevier BV, 2012-01-01) Multimedia indexing and retrieval has become a challenging topic in organizing huge amount of multimedia data. This problem is not a trivial task for large visual databases; hence, segmentation into low- and high-level temporal video segments might improve the realization of this task. In this paper, we introduce a weighted undirected graph-based movie scene detection approach to detect semantically meaningful temporal video segments. The method is based on the idea of finding the dominant scene of the vide...

Citation Formats

E. Acar, S. Arslan, A. Yazıcı, and M. KOYUNCU, “Slim-Tree and BitMatrix index structures in image retrieval system using MPEG-7 Descriptors,” 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40034.