Overall the appearance of skewed lines with different orientation

Overall the appearance of skewed lines with different orientation and text lines close to each other make handwritten text less readable.From the third above, printed and handwritten text are characterized by their feature diversity. Hence, their text line segmentation as well as parameter extraction procedure can be quite dissimilar, although algorithms Inhibitors,Modulators,Libraries should fulfill these tasks for printed as well as for handwritten text.Prior to text parameter extraction, text line segmentation should be done. It is an important step in document image processing. Although some text line detection techniques are successful in printed documents, processing of handwritten documents has remained a key problem in OCR [1,2]. Most text line segmentation methods are based on the assumptions that the distance between neighboring text lines is significant and that text lines are reasonably straight.

However, these assumptions are not always valid for handwritten documents. Hence, text line segmentation is a leading challenge in document image analysis Inhibitors,Modulators,Libraries [3].Upon completion of this process, the primary goal of OCR is the extraction of text parameters from optically scanned documents, so reference text line and skew rate identification is mandatory. Their validity is of major importance for any OCR process. There are various reasons for the appearance of multi-skewed lines in text, but two of them are the most common [1]: Firstly, some degree of misalignment of the document during the scanning process is unavoidable, but since all printed text lines Inhibitors,Modulators,Libraries in the scanned document are uniformly skewed, this way the reference text lines are almost parallel.

Secondly, text lines in an original handwritten document are skewed differently due to specific individual handwriting habits, so handwriting text lines present different orientations, Inhibitors,Modulators,Libraries i.e., they are multi-skewed. To enhance the ability of document analysis system, we need a robust algorithm for text line segmentation as well as for parameter extraction.Many proposed algorithms have been evaluated by quite different test methods. In fact, these evaluation procedures are usually based on use of a custom text database as a test sample. Accordingly, testing result interpretation is quite dissimilar [4]. Hence, the establishment of the test framework for the evaluation of the document image processing algorithms is of great Carfilzomib importance.

This is precisely the task of this paper, and a basic method framework for the evaluation of the text line segmentation and text parameters extraction click here is proposed.The paper is organized as follows: in Section 2 the test framework is presented. It is divided into two test groups. Each of them is completely described. Section 3 contains an examination and evaluation of the test framework procedure using an example of the specific algorithm. A Gaussian isotropic kernel is used as the basic test algorithm. Results are analyzed, examined and discussed. Conclusions are given in Section 4.2.

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