Content-Based Similar Image Retrieval Using Wavelet Packet Transform

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  • ウェーブレットパケット変換による内容に基づく類似画像検索
  • ウェーブレットパケット ヘンカン ニ ヨル ナイヨウ ニ モトズク ルイジ ガゾウ ケンサク

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Abstract

The content-based image retrieval system is a technique for retrieving images on the basis of automatically extracted features such as color, texture and shape. In this paper, we propose a similar image retrieval method by the wavelet packet transform for feature extraction of an image. The wavelet packet transform enables good approximation of an image because it allows better frequency resolution and much higher precision and flexibility in the selection of the bases. A query and all database images are transformed into the wavelet packet bases by the wavelet packet transform, and the optimal bases are chosen from the full-quad wavelet packet tree by the best basis algorithm. The structure of the optimal wavelet packet tree for similar images tends to be similar to each other. Our retrieving algorithm makes use of the structure of this wavelet packet tree and Euclid distance. The experiments were performed on the very large-image database containing 60,000 images from Corel Gallery. We evaluate the ability of our proposed retrieval method using a Recall-Precision graph. From this result, it is clarified that our proposed method provides greater accuracy, average Recall 25.96% and average Precision 60.0%. We also indicated that it is possible to easily obtain similar images from the very large-image database.

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