Automatic Machine Interactions for Content-Based Image Retrieval Using A Self-Organizing Tree Map Architecture  

Oleh:

Muneesawang, P. ; Guan, Ling

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 4 (2002), page 821-834.
Topik: ARCHITECTURE; automatic machine; interactions; content -based image; self - organizing tree map; architecture

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.7A Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this paper, an unsupervised learning network is explored to incorporate a self -learning capability into image retrieval systems. Our proposal is a new attempt to automate recursive content - based image retrieval. The adoption of a self - organizing tree map (SOTM) is introduced, to minimize the user participation in an effort to automate interactive retrieval. The automatic learning mode has been applied to optimize the relevance feedback (RF) method and the single radial basis function - based RF method. In addition, a semiautomatic version is proposed to support retrieval with different user subjectivities. Image similarity is evaluated by a nonlinear model, which performs discrimination based on local analysis. Experimental results show robust and accurate performance by the proposed method, as compared with conventional noninteractive content - based image retrieval (CBIR) systems and user controlled interactive systems, when applied to image retrieval in compressed and uncompressed image databases.

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