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Improved algorithm for blob detection in document images

机译:改进的文档图像斑点检测算法

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This paper proposes a fast algorithm for blob detection for document images. Blobs are connected components in a binary image. Blobs need to be detected and extracted in order to obtain useful information from image. Blobs may be 4-connected or 8-connected. Various algorithms are proposed for detecting blobs [5]. As it is the backbone of all fundamental operations, it needs to be fast and accurate. Proposed algorithm makes use of the fact that most document images have more background units as compared to foreground units. Processing them unit by unit is more time consuming. So, algorithm works by processing them in blocks where each block consists of 8 units. In this way, numbers of comparisons are reduced significantly. Also the paper compares the proposed algorithm with five other algorithms on the basis of image size and execution time. Reduced number of comparisons makes it nearly 1.5 times faster than algorithms discussed in paper.
机译:本文提出了一种用于文档图像斑点检测的快速算法。 Blob是二进制映像中的连接组件。需要检测并提取斑点,以便从图像中获取有用的信息。 Blob可以是4连接或8连接的。提出了各种算法来检测斑点[5]。由于它是所有基本操作的中坚力量,因此必须快速而准确。提出的算法利用了这样的事实,即与前景单元相比,大多数文档图像具有更多的背景单元。逐个处理它们比较耗时。因此,算法通过在每个块包含8个单位的块中对其进行处理来工作。这样,比较的数量大大减少了。本文还根据图像大小和执行时间将提出的算法与其他五种算法进行了比较。减少的比较数量使其比论文中讨论的算法快近1.5倍。

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