Image Retrieval Using Cubic Splies Neural Networks

نویسندگان

  • Samy Sadek
  • Ayoub Al-Hamadi
  • Bernd Michaelis
چکیده

Most of the approaches of Content-Based Image Retrieval (CBIR) presume a linear relationship between different image features, and the efficiency of such systems was limited due to the difficulty in representing high-level concepts using low-level features. In this paper, a new architecture for a CBIR system is proposed; the Splines Neural Network-based Image Retrieval (SNNIR) system. SNNIR makes use of a rapid and precise network model that employs a cubic-splines activation function. By using the cubic-splines network, the proposed system could determine nonlinear relationship between images features so that more accurate similarity comparison between images can be supported. Experimental results show that the proposed system achieves high accuracy and effectiveness in terms of precision and recall compared to other CBIR systems. Index Term — Splines neural network, Feature extraction, Content-based image retrieval.

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تاریخ انتشار 2013