Detection of Image Fragments Related by Affine Transforms: Matching Triangles and Ellipses

M. Paradowski, A. Sluzek
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引用次数: 8

Abstract

Visual information retrieval systems are often constructed upon the notion of image similarity. The concept of image similarity may be defined in many ways: from a pure visual level, where we seek identical images, to a semantic level related with human perception the image. In our research we address the first approach, we explore topics of image matching (image alignment), however in terms of image fragments. The goal of image fragment matching is to find similar parts of two images, without a given model of particular objects present on images. It is also assumed that the number of similar objects (image fragments) is not known. In this paper we present a novel method for image fragment matching. It uses two ellipse pairs as an elementary object for image geometry reconstruction. The method is an extension of the previously proposed approach based on triangles. We have decided to replace triangles with a different geometrical structure to reduce computational complexity from O(n^3) to O(n^2), where n is the number of coherent key regions. We discuss and compare both matching methods both in terms of quality and processing efficiency.
仿射变换相关图像片段的检测:三角形和椭圆的匹配
视觉信息检索系统通常建立在图像相似度的概念之上。图像相似性的概念可以从许多方面来定义:从纯粹的视觉层面,我们寻求相同的图像,到与人类感知图像相关的语义层面。在我们的研究中,我们解决了第一种方法,我们探索了图像匹配(图像对齐)的主题,但是在图像片段方面。图像片段匹配的目标是找到两幅图像的相似部分,而不需要给定图像上特定物体的模型。我们还假设相似物体(图像片段)的数量是未知的。本文提出了一种新的图像片段匹配方法。它使用两个椭圆对作为图像几何重构的基本对象。该方法是先前提出的基于三角形的方法的扩展。我们决定用不同的几何结构替换三角形,以将计算复杂度从O(n^3)降低到O(n^2),其中n是相干关键区域的数量。从质量和加工效率两个方面对两种匹配方法进行了讨论和比较。
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