Adaboost算法集成颜色和纹理特征的图像检索技术

摘要

Feature extraction is one of the key steps in content-based image retrieval, but one teature based approach expresses only partial attributes of an image, which unilaterally describes the image content and is short of enough resolving power. This method may not achieve ideal result in the case of images varying greatly. Taking advantage of adaboost algorithm and relevance feedback mechanism, a technology was proposed based on image color and texture features. The experiment shows that the approach has good retrieval performance.%特征提取是图像检索的关键步骤，针对仅基于一种特征只能表达图像的部分属性，并且在多分类问题中，对图像内容的描述比较片面。缺乏足够的分辨能力。在图像类别较多，并且图像变化较大的场合不能取得理想的检索效果。基于相关反馈检索机制，提出了一种由Adaboost算法集成颜色和纹理特征的相关反馈图像检索方法。实验结果表明。通过反馈机制的Adaboost算法集成组合特征进行图像检索，该方法有较好的检索性能。