文章基本信息

标题：Efficient Item Image Retrieval System
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作者：S. Adebayo Daramola ; Ademola Abdulkareem ; K. Joshua Adinfona 等
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2014
卷号：4
期号：2
页码：109-113
出版社：International Journal of Soft Computing & Engineering
摘要：Content based image retrieval system is a very effective means of searching and retrieving similar images from large database. This method is faster and easy to implement compare to text based image retrieval method. Ability to extract discriminative low level feature from these images and use them with appropriate classifier is factor in determining retrieval result. In this work efficient item image retrieval system is proposed. The system utilizes Haar wavelet transform, Phase Congruency and Support Vector Machine. Haar wavelet transform acted on image to form four sub-images. Texture feature is extracted from smaller image blocks from detailed bands and it was combined with shape feature from approximation band to form feature vector. Feature distance margin is achieved between query image and images in the database using Support Vector Machine (SVM). The effectiveness of the system is confirmed from output retrieval results.
关键词：Content; Texture; shape; Support Vector;Machine; Phase Congruency