کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
525970 869047 2012 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Incorporating multiple distance spaces in optimum-path forest classification to improve feedback-based learning
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Incorporating multiple distance spaces in optimum-path forest classification to improve feedback-based learning
چکیده انگلیسی

In content-based image retrieval (CBIR) using feedback-based learning, the user marks the relevance of returned images and the system learns how to return more relevant images in a next iteration. In this learning process, image comparison may be based on distinct distance spaces due to multiple visual content representations. This work improves the retrieval process by incorporating multiple distance spaces in a recent method based on optimum-path forest (OPF) classification. For a given training set with relevant and irrelevant images, an optimization algorithm finds the best distance function to compare images as a combination of their distances according to different representations. Two optimization techniques are evaluated: a multi-scale parameter search (MSPS), never used before for CBIR, and a genetic programming (GP) algorithm. The combined distance function is used to project an OPF classifier and to rank images classified as relevant for the next iteration. The ranking process takes into account relevant and irrelevant representatives, previously found by the OPF classifier. Experiments show the advantages in effectiveness of the proposed approach with both optimization techniques over the same approach with single distance space and over another state-of-the-art method based on multiple distance spaces.


► Two feedback-based learning methods based on OPF and multiple distance space.
► They solve image retrieval in a few iterations of relevance feedback.
► Considerable gains in effectiveness are demonstrated.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 116, Issue 4, April 2012, Pages 510–523
نویسندگان
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