基于边缘切线流场的多尺度结构张量图像检索算法

Multi-Scale Structure Tensor Image Retrieval Algorithm Based on Edge Tangent Flow Field

为减小基于草图的检索技术中弱边缘的影响并提高特征的平移不变性,提出了一种基于边缘切线流场的多尺度结构张量检索算法.该算法采用边缘切线流场取代梯度场,在显著强边缘上计算结构张量以抑制弱边缘的影响,并在多尺度分区架构下进行结构张量特征的提取以增强特征的平移不变性.实验结果表明,与传统的结构张量方法相比,该算法有效地抑制了弱边缘的影响,避免了使用图像梯度方向描述图像显著边缘方向的不稳定性,增强了特征的平移不变性,提高了检索性能.

In order to reduce the effects of weak edges and reinforce the shift invariance in sketch-based image retrieval（ SBIR）,a multi-scale structure tensor retrieval algorithm on the basis of edge tangent flow field is proposed. In this algorithm,edge tangent flow field is used as a substitute for the gradient map of image,and the structure tensor is calculated directly on remarkable strong edges to suppress the effects of weak edges. Besides,structure tensor feature is extracted in the form of multi-scale partition to enhance the shift invariance. Experimental results indicate that the proposed algorithm is superior to the existing structure tensor method because it helps suppress the effects of weak edges effectively,avoid instable significant edge of image described by image gradient direction,enhance the shift invariance of structure,and,thereby,improve the retrieval efficiency.