Saturday, October 5, 2013

Color Encoding of Multiple Layout Levels.

An example image to demonstrate color encoding of multiple layout levels. The images show word level and text-line level segmentation.




Different Performance Measures

Example image to illustrate different performance measures. The left image shows two color coded document images. A pixel correspondence graph obtained from these images is shown on the right side. The nodes corresponding to the ground-truth segments are labeled 1-7, whereas the nodes in the segmented image are labeled a-i. Only significant edges are shown in the pixel correspondence graph. Based on the definitions given in Section II-C, the values of each performance measure for this example are given on the right side of the graph.

Literature Survey

Performance Evaluation and Benchmarking

of Six Page Segmentation Algorithms

  •  This paper give an idea about performance of the famous six segmentation algorithms namely Dummy algorithm, X-Y Cut, Smearing, Whitespace analysis, Constrained text-line detection and Voronoi-diagram based algorithm in various types of input images.   
  • This paper deliver a good method for evaluating The performance of Segmentation algorithm.  and  
  • This paper concludes such a way that which algorithm is best for  which types of input images. For eg. the x-y cut and the smearing algorithms fail to segment a page in the presence of noise. The whitespace analysis algorithm is sensitive to the stopping rule and results in either over-segmentations of under-segmentations. The docstrum and the Voronoi algorithms tend to over-segment title and section headings if the font size is much different from body text in that page. The constrained text-line finding algorithm misses single-digit page numbers as it requires at least two components to make a line.


Thursday, October 3, 2013

Document Image Analysis

The objective of document image analysis is to recognize the text and graphics components in images of documents, and to extract the intended information as a human would.