Image Retrieval Using Data Mining Technique

Authors

  • Sarmad T. Abdul-Samad Department of Computer Science, College of Science, AL-Nahrain University, Baghdad, Iraq
  • Sawsan Kamal Department of Computer Science, College of Science, AL-Nahrain University, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2020.61.8.26

Keywords:

CBIR, HSV 3D Histogram, GLCM, Fuzzy c-means clustering

Abstract

Even though image retrieval is considered as one of the most important research areas in the last two decades, there is still room for improvement since it is still not satisfying for many users. Two of the major problems which need to be improved are the accuracy and the speed of the image retrieval system, in order to achieve user satisfaction and also to make the image retrieval system suitable for all platforms. In this work, the proposed retrieval system uses features with spatial information to analyze the visual content of the image. Then, the feature extraction process is followed by applying the fuzzy c-means (FCM) clustering algorithm to reduce the search space and speed up the retrieval process. The experimental results show that using the spatial features increases the system accuracy and that the clustering algorithm speeds up the image retrieval process. This shows that the proposed system works with texture and non-texture images.

 

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Published

2020-08-28

Issue

Section

Computer Science

How to Cite

Image Retrieval Using Data Mining Technique. (2020). Iraqi Journal of Science, 61(8), 2115-2125. https://doi.org/10.24996/ijs.2020.61.8.26

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