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Invarint Image Retrieval using Block-Based Visual Pattern Matching

机译:使用基于块的可视模式匹配的virarint图像检索

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This paper proposes an object-based image retrieval using a method based on visual pattern matching. A visual pattern is obtained by detecting the line edge from a square block using the moment-preserving edge detector. It is desirable and yet remains as a challenge for querying multimedia data by finding an object inside a target image. Given an object model, an added difficulty is that the object might be translated, rotated, and scaled inside a target image. Instead of segmentation and detailed object representation, the objective of this research is to develop and apply computer vision methods that explore the structure of an image object by visual pattern detection to retrieve images from a database. A voting scheme based on generalized Hough transform is proposed to provide object search method, which is invariant to the translation, rotation, scaling of image data. Computer simulation results show that the proposed method gives good performance in terms of retrieval accuracy and robustness
机译:本文提出了一种使用基于视觉模式匹配的方法的基于对象的图像检索。通过使用时刻保留边缘检测器检测来自方块的线边缘来获得视觉模式。它是可取的,并且仍然是通过在目标图像内找到对象来查询多媒体数据的挑战。给定对象模型,增加的难度是对象可以在目标图像内转换,旋转和缩放。该研究的目的是通过视觉模式检测开发和应用探索图像对象的结构的计算机视觉方法来开发和应用探索图像对象的结构以从数据库中检索图像。提出了一种基于广义Hough变换的投票方案,提供了对象搜索方法,其不变于翻译,旋转,图像数据的缩放。计算机仿真结果表明,该方法在检索准确性和鲁棒性方面具有良好的性能

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