基于梯度方向直方图金字塔的图像形状检索方法

2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC) Pub Date : 2019-03-01 DOI:10.1109/ICCPEIC45300.2019.9082407

Sanket Bhave, A. Giri, Shravan Bhavsar

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引用次数: 0

摘要

基于形状的图像检索(SBIR)是一种通过提取物体的形状特征从数据库中检索图像的技术。该方法首先提取形状特征，然后根据一定的度量进行相似度匹配。有向梯度直方图金字塔(PHOG)是有向梯度直方图(HOG)的改进版本，对于图像特征向量的计算非常有效。在本文中，PHOG和位置敏感哈希作为一种新的SBIR方法被利用。局部敏感哈希(Locality Sensitive hash, LSH)用于位级相似性匹配。

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Effective method for Shape based Image Retrieval using Pyramid of Histogram of Oriented Gradients

Shape Based Image Retrieval (SBIR) is a technique to retrieve images from the database by extracting the shape features of the object. In SBIR, shape features are extracted and then similarity matching is carried out based on some measure. Pyramid of Histogram of Oriented Gradients (PHOG), an improvised version of Histogram of Oriented Gradients (HOG), is very efficient for calculation of feature vector of an image. In this paper, PHOG along with Locality Sensitive Hashing has been exploited as a novel approach to SBIR. Locality Sensitive Hashing (LSH) is used for bit-level similarity matching.

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2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)

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