Arslan, Sarper

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https://hdl.handle.net/20.500.14411/7203
Name Variants
Arslan,S.
A.,Sarper
S.,Arslan
A., Sarper
Sarper, Arslan
Arslan, Sarper
S., Arslan
Job Title
Araştırma Görevlisi
Email Address
sarper.arslan@atilim.edu.tr
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Avionics
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2

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7

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1

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3.50

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2008 International Workshop on Content-Based Multimedia Indexing, CBMI 2008, Conference Proceedings -- 2008 International Workshop on Content-Based Multimedia Indexing, CBMI 2008 -- 18 June 2008 through 20 June 2008 -- London -- 734502
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  • Thumbnail Image
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    Citation - Scopus: 7
    Slim-Tree and Bitmatrix Index Structures in Image Retrieval System Using Mpeg-7 Descriptors
    (2008) Açar,E.; Arslan,S.; Yazici,A.; Koyuncu,M.
    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. ©2008 IEEE.
  • Thumbnail Image
    Conference Object
    Slim-Tree and Bitmatrix Index Structures in Image Retrieval System Using Mpeg-7 Descriptors
    (2008) Açar,E.; Arslan,S.; Yazici,A.; Koyuncu,M.
    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. ©2008 IEEE.