NDLI: Image retrieval by region of interest motif co-occurence matrix

Content Provider	IEEE Xplore Digital Library
Author	Yen-Shin Lee Shu-Sheng Hao Shu-Wei Lin Sheng-Yi Li
Copyright Year	2012
Description	Author affiliation: Department of Electronic and Electrical Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan County, 33551, Taiwan (Yen-Shin Lee; Shu-Sheng Hao; Shu-Wei Lin; Sheng-Yi Li)
Abstract	Because of the fast developing technologies in multimedia devices, we are able to receive huge amounts of images from daily life. Once these images have been stored, the next step is to figure out how to retrieve the desired pictures quickly and accurately from the database. In this paper, we intend to develop an efficient image retrieval algorithm. Using this algorithm, we can retrieve desired images by using similar input sample images. Our research images include vehicles, buildings, flowers and other natural scenes. First, we applied the edge and morphological filter on the grey scale images to refill and extract the largest interesting object from the image. Second, we developed an image retrieval algorithm called Region of Interest (ROI) Motif Co-occurrence Matrix (RMCM) to find the relation of the neighboring pixels on the image. In this algorithm, we need to generate a 2 × 2 pattern called a motif. The main idea of this algorithm is to quickly and accurately find the characteristic values about motif. Finally, we can compare the Euclidean distance of the characteristic values from the motif to locate the most similar image from database. In our develop algorithm we combine the partly area motif and characteristic area center location methods to raise the accuracy and speed of recognition. Using our proposed algorithm RMCM, the mean processing time is about 0.82 seconds per image. This value is faster than using Motif Co-occurrence Matrix (MCM) by about 2.57 times. The accurate recognition rates are about 95% and 87% as related to vehicles and buildings.
Starting Page	270
Ending Page	274
File Size	583626
Page Count	5
File Format	PDF
ISBN	9781467350839
e-ISBN	9781467350822
e-ISBN	9781467350815
DOI	10.1109/ISPACS.2012.6473494
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-04
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image retrieval Image edge detection Signal processing algorithms Image color analysis Algorithm design and analysis Artificial intelligence Signal processing Peano scan Texture Recognition Motif Co-occurrence Matrix Color histogram Content based Retrieval
Content Type	Text
Resource Type	Article

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