多特征组合和用户反馈的图像检索算法

Image Retrieval Algorithm Based on Multi-feature Combination and User Feedback

针对单一特征只能描述图像内容部分信息的缺陷,为获得更高准确率的图像检索结果,设计一种基于多特征组合和用户反馈相融合的图像检索算法.首先提取图像的多种特征,将其组合形成图像检索的特征向量,并采用欧氏距离计算图像间的相似度,实现图像初步检索;然后通过用户对图像初步检索结果进行评价和反馈,并采用机器学习算法根据反馈结果对图像初步检索结果进行调整,实现图像的精确检索;最后采用图像库检索的标准数据进行仿真测试.测试结果表明,该算法获得了稳定的图像检索结果,图像检索准确率明显高于其他算法.

Aiming at the defects of single feature that could only describe the partial information of image content.In order to obtain more accurate image retrieval results,we designed an image retrieval algorithm based on multi-feature combination and user feedback.Firstly,many features of the image were extracted and combined to form a feature vector for image retrieval,the Euclidean distance was used to calculate the similarity between images,and the initial image retrieval was realized.Secondly,through the evaluation and feedback of the initial image retrieval results,the machine learning algorithm was used to adjust the initial image retrieval results according to the feedback results,so as to achieve accurate image retrieval.Finally,the standard data of image library retrieval were simulated and tested.The test results show that the proposed algorithm achieves stable image retrieval results,and the accuracy of image retrieval is obviously higher than other algorithms.