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A novel method for extracting and recognizing logos

机译:一种提取和识别徽标的新方法

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摘要

Nowadays, the high volume of archival documents has made it exigent to store documents in electronic databases. A text logo represents the ownership of the text, and different texts can be categorized by it; for this reason, different methods have been presented for extracting and recognizing logos. The methods presented earlier, suffer problems such as, error of logo detection and recognition and slow speed. The proposed method of this study is composed of three sections: In the first section, the exact position of the logo can be identified by the pyramidal tree structure and horizontal and vertical analysis, and in the second section, the logo can be extracted through the algorithm of the boundary extension of feature rectangles. In the third section, after normalizing the size of the logo and eliminating the skew angle, for feature extraction, we first blocked the region encompassing the logo, and then we extract a particular feature by the parameter of the center of gravity of connected component each block. Finally, we use the KNN classification for the recognition of the logo.
机译:如今,大量的存档文件使其迫切需要将文档存储在电子数据库中。文字徽标表示该文字的所有权,并且可以按其分类不同的文字;由于这个原因,已经提出了用于提取和识别徽标的不同方法。较早提出的方法遭受诸如徽标检测和识别的错误以及速度慢的问题。本研究提出的方法包括三个部分:第一部分,可以通过金字塔树结构和水平和垂直分析来确定徽标的确切位置,第二部分可以通过徽标提取徽标。特征矩形边界扩展算法。在第三部分中,在对徽标的大小进行了标准化并消除了偏斜角之后,对于特征提取,我们首先对包含徽标的区域进行了遮挡,然后通过每个连接组件的重心参数来提取特定的特征块。最后,我们使用KNN分类识别徽标。

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