There is an ever increasing number of publications which do not have the “traditional” layout where printed regions are rectangular. Text paragraphs and areas of graphic type may be of any shape, individually rotated and in any arrangement. Previous document analysis techniques are not well suited to such complex layouts. This paper introduces a new method for the segmentation of images of docu...

In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of his...

This paper presents a unified algorithm for segmentation and identification of various tabular structures from document page images. Such tabular structures include conventional tables and displayed mathzones, as well as Table of

This paper explores the use of script identification vectors in the analysis of multilingual document images. A script identification vector is calculated for each connected component in a document. The vector expresses the closest distance between the component and templates developed for each of thirteen scripts, including Arabic, Chinese, Cyrillic, and Roman. We calculate the first three pri...

The web page usage mining plays a vital role in enriching the page’s content and structure based on the feedbacks received from the user’s interactions with the page. This paper proposes a model for micro-managing the tracking activities by fine-tuning the mining from the page level to the segment level. The proposed model enables the web-master to identify the segments which receives more focu...

This paper explores the effectiveness of different semantic web page segmentation algorithms on modern websites. We compare three known algorithms each serving as an example of a particular approach to the problem, and one self-developed algorithm, WebTerrain, that combines two of the approaches. With our testing framework we have compared the performance of four algorithms for a large benchmar...

We consider in this paper the problem of complex handwritten page segmentation such as novelist drafts or authorial manuscripts. We propose to use stochastic and contextual models in order to cope with local spatial variability, and to take into account some prior knowledge about the global structure of the document image. The models we propose to use are Markov Random Field models. Using this ...

This paper presents a quantitative comparison of six algorithms for page segmentation: X-Y cut, smearing, whitespace analysis, constrained text-line finding, Docstrum, and Voronoi-diagram-based. The evaluation is performed using a subset of the UW-III collection commonly used for evaluation, with a separate training set for parameter optimization. We compare the results using both default param...

Objectives: To improve the efficiency of tri-level segmentation tasks for handwritten Gujarati text. Methods: Using hybrid methods segmentation, we have used line, word and character from image. This study presents a paradigm that works with touching characters, slop line written on page, overlapping, etc. It evaluated dataset 500+ images created by us different writing sentences people. We Hor...

In this paper we describe a method for the expansion of training sets made by XY trees representing page layout. This approach is appropriate when dealing with page classification based on MXY tree page representations. The basic idea is the use of tree grammars to model the variations in the tree which are caused by segmentation algorithms. A set of general grammatical rules are defined and us...