A Combined Approach to SBIR using Edge Histogram Descriptor with Contourlet Transform

N. Chaudhary
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引用次数: 1

Abstract

This paper focuses on the problem of efficient and fast retrieval of images from a large database using sketch as query image. Basically searching is based on a descriptor that addresses the asymmetry between binary sketch from the user side and full color image of the database. The working of proposed algorithm is such that query image and full color database images undergo same feature extraction process. Database images will be clustered offline which reduces time complexity on runtime. Further indexing is done which will be used to describe, store and organize image information and to assist people in finding image resources conveniently and quickly. Firstly feature vector extraction is done using contours and then edges will be detected in different orientation using modulus maxima edge detection in contourlet domain. This approach is almost better than existing approaches in many aspects such as compactness of feature vector, simplicity of implementation, retrieval performance and efficient feature extraction less time complexity.
边缘直方图描述子与Contourlet变换相结合的SBIR方法
本文主要研究以速写作为查询图像从大型数据库中高效快速检索图像的问题。基本上,搜索是基于一个描述符来解决来自用户端的二进制草图和数据库的全彩图像之间的不对称。该算法的工作原理使查询图像与全彩数据库图像进行相同的特征提取过程。数据库映像将离线聚类,从而降低运行时的时间复杂度。进一步的索引将用于描述、存储和组织图像信息,帮助人们方便、快速地查找图像资源。首先利用轮廓进行特征向量提取,然后在contourlet域中利用模极大值边缘检测在不同方向上检测边缘。该方法在特征向量紧凑性、实现简单性、检索性能、特征提取效率高、时间复杂度低等方面几乎优于现有方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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