基于边缘检测的多特征智能图像检索模型

Multi-feature intelligent image retrieval model based on edge detection

  • 摘要: 提出一种智能图像二级检索模型.第一级检索利用改进的Canny算子和颜色向量角分别检测图像边缘,再基于db2小波进行图像融合得到二值边缘,并运用图像位错率进行边缘信息比较,将相似度大的图像组成一个新的备选图像库,以缩小图像检索范围.然后利用HSI颜色不变量模型改进颜色相关矩阵,加以边缘直方图进行综合特征第二级检索.实验表明该模型能够准确和高效地查找出用户所需内容的彩色图像,并且具有较好的准确率和回想率.

     

    Abstract: Two-stage intelligent image retrieval model is proposed. In the first rank the model detects the edge of original image by the means of new Canny operator and color vector angle respectively, and then it conducts image fusion of the two results that produced by those two detection methods based on db2 wavelet, and finally bit error rate is used to compare the similarity of edge information in order to narrow the retrieval range, which turned out a new alternative image library. In the second rank HSI color invariant model is used to improve the color correlation matrix for multi-feature image retrieval with edge histogram. Experimental results show that our model is accurate and efficient in the user-interested images retrieval with better precision and recall.

     

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