Sketch4match -使用草图的基于内容的图像检索系统

B. Szanto, P. Pozsegovics, Z. Vámossy, S. Sergyán
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引用次数: 47

摘要

基于内容的图像检索(CBIR)是数字图像处理领域中最受欢迎的新兴研究领域之一。大多数可用的图像搜索工具,如Google Images和Yahoo!图像搜索,是基于图像的文本注释。在这些工具中,用关键字手动标注图像,然后使用基于文本的搜索方法检索图像。这些系统的性能并不令人满意。CBIR的目标是自动提取图像的视觉内容,如颜色、纹理或形状。本文旨在介绍基于手绘草图的图像检索系统(sketch based image retrieval - SBIR)的设计和创建过程中遇到的问题和挑战。在现有方法的帮助下,描述了一种可能的解决方案,即如何设计和实现一个特定于任务的描述符,该描述符可以处理草图和彩色图像之间的信息差距,从而为高效搜索提供机会。所使用的描述符是在经过特殊的预处理步骤序列后构建的,可以将变换后的全彩图像与草图进行比较。我们学习了EHD, HOG和SIFT。在两个样本数据库上的实验结果显示了良好的效果。总体而言,结果表明,基于草图的系统允许用户直观地访问搜索工具。SBIR技术可用于数字图书馆、预防犯罪、照片共享网站等多种应用。这一制度在法医学和执法中对逮捕犯罪嫌疑人和识别受害者具有重要价值。一个可能的应用是将法医素描与一组嫌疑犯照片进行比对。近年来,基于查询图像的视觉内容检索图像的领域日益扩大,这就对图像处理领域提出了相当广泛的方法论要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sketch4match — Content-based image retrieval system using sketches
The content based image retrieval (CBIR) is one of the most popular, rising research areas of the digital image processing. Most of the available image search tools, such as Google Images and Yahoo! Image search, are based on textual annotation of images. In these tools, images are manually annotated with keywords and then retrieved using text-based search methods. The performances of these systems are not satisfactory. The goal of CBIR is to extract visual content of an image automatically, like color, texture, or shape. This paper aims to introduce the problems and challenges concerned with the design and the creation of CBIR systems, which is based on a free hand sketch (Sketch based image retrieval — SBIR). With the help of the existing methods, describe a possible solution how to design and implement a task spesific descriptor, which can handle the informational gap between a sketch and a colored image, making an opportunity for the efficient search hereby. The used descriptor is constructed after such special sequence of preprocessing steps that the transformed full color image and the sketch can be compared. We have studied EHD, HOG and SIFT. Experimental results on two sample databases showed good results. Overall, the results show that the sketch based system allows users an intuitive access to search-tools. The SBIR technology can be used in several applications such as digital libraries, crime prevention, photo sharing sites. Such a system has great value in apprehending suspects and indentifying victims in forensics and law enforcement. A possible application is matching a forensic sketch to a gallery of mug shot images. The area of retrieve images based on the visual content of the query picture intensified recently, which demands on the quite wide methodology spectrum on the area of the image processing.
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