A New Visual Vocabulary for Object Recognition

International journal of new computer architectures and their applications Pub Date : 1900-01-01 DOI:10.17781/p002449

I. Sayad

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引用次数: 0

Abstract

Images can be represented at different levels, many approaches in the domain of image representation were developed to move from low-level to high-level image representation like Collocation patterns (moving from Visual Words to Visual Phrases), Descriptive Visual Words and Phrases (DVWs & DVPs) for Image applications and Recognition Using Visual Phrases. Moreover, many relevant articles have tackled the problem of image representation in the case of image retrieval. These articles showed advantages and disadvantages of the used methods in addressing the problem of image representation. The main purpose of this paper is to tackle these drawbacks based on the performance of image representation. What lacks in other papers is the semantic learning and not considering the spatial location of the region. In this paper, a development is proposed for a semantic coherent visual word pattern representation that considers three main points, the neighbor among visual words, frequent item set among these visual words, and the semantic learning. Keywords—BOW; Image Representation; DVW; DVP; Image Processing; Image Retrieval; Visual Words

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一种新的物体识别视觉词汇

图像可以在不同的层次上表示，许多图像表示领域的方法被开发出来，从低级到高级的图像表示，如搭配模式(从视觉单词移动到视觉短语)，用于图像应用的描述性视觉单词和短语(dvw & dvp)和使用视觉短语进行识别。此外，许多相关文章已经解决了图像检索中的图像表示问题。这些文章展示了用于解决图像表示问题的方法的优点和缺点。本文的主要目的是在图像表示性能的基础上解决这些缺点。其他文献缺乏的是语义学习，没有考虑区域的空间位置。本文提出了一种语义连贯的视觉词模式表示方法，该方法主要考虑三个方面:视觉词之间的相邻关系、视觉词之间的频繁项集和语义学习。Keywords-BOW;图像表示;DVW;实施;图像处理;图像检索;视觉单词

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International journal of new computer architectures and their applications

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