COLOR-FREQUENCY-ORIENTATION HISTOGRAM BASED IMAGE RETRIEVAL

被引：0

作者：

Zhang, Zhuo ^{[1
]}

Gu, Xiaodong ^{[1
]}

Kung, Sunyuan ^{[1
]}

机构：

[1] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2012年

关键词：

Image classification; image retrieval; color-frequency-orientation histogram; support vector machines (SVMs);

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper proposes a multiclass image retrieval method using combined color-frequency-orientation histogram. Shape information, obtained via edge detector and Hough Transform, is also incorporated into the new feature. The feature has shown advantage in both unsupervised and supervised learning on Corel image dataset containing 10 categories of 1000 complex scenes. In unsupervised learning, comparing with histogram-based method [1], SIMPLIcity [2], FIRM [3], edge-based method [4], multi-resolution-based method [5], our approach respectively shows 25%, 14%, 10%, 7% and 2% improvement in accuracy. In supervised learning, we implement both one-against-one SVM and one-against-all SVM for multiclass classification. One-against-all SVM beats one-against-one SVM, achieving 95% accuracy with sufficient training.

引用

页码：1321 / 1324

页数：4

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