Wavelet Based Page Segmentation

IEEE Transactions on Image Processing, 2007

In this paper, we have proposed a novel scheme for the extraction of textual areas of an image using globally matched wavelet filters. A clustering-based technique has been devised for estim ating globally matched wavelet filters using a collection of groundtruth images. We have extended our text extraction scheme for the segmentation of document images into text, background, and picture components (which include graphics and continuous tone images). Multiple, two-class Fisher classifiers have been used for this purpose. We also exploit contextual information by using a Markov random field formulation-based pixel labeling scheme for refinement of the segmentation results. Experimental results have established effectiveness of our approach.

2001

This paper presents a new model-based document image segmentation scheme that uses XML-DTDs (eXtensible Markup Language Document Type Definitions). Given a document image, the algorithm has the ability to select the appropriate model. A new wavelet-based tool has been designed for distinguishing text from non-text regions and characterization of font sizes. Our model-based analysis scheme makes use of this tool for identifying the logical components of a document image

Signal processing, 1995

role in office automation, especially in intelligent signal processing. In this paper, we propose an intelligent document analysis system to achieve the document segmentation and identification goal. The proposed system consists of two modules: block segmentation and block identification. In our approach, we first segment a document into several non-overlapping blocks by utilizing a novel recursive segmentation technique, then extract the features embedded in each segmented block. Two kinds of features, connectivity histogram and multiresolution features, are extracted. The features are verified to be effective in characterizing document blocks. Last, a two-layer perceptron is adopted in the identification module to determine the identity of the considered block. Experiments with a wide varity of documents verify the feasibility of our approach.

Document Analysis Systems VII, 2006

Pattern Recognition, 2006. …, 2006

International Journal of Wavelets, Multiresolution and Information Processing, 2003

This paper proposes a novel algorithm to clean up a large collection of historical handwritten documents kept in the National Archives of Singapore. Due to the seepage of ink over long period of storage, the front page of each document has been severely marred by the reverse side writing. Earlier attempts have been made to match both sides of a page to identify the offending strokes originating from the back so as to eliminate them with the aid of a wavelet transform. Perfect matching, however, is difficult due to document skews, differing resolutions, inadvertently missing out reverse side and warped pages during image capture. A new approach is now proposed to do away with double side mapping by using a directional wavelet transform that is able to distinguish the foreground and reverse side strokes much better than the conventional wavelet transform. Experiments have shown that the method indeed enhances the readability of each document significantly after the directional wavelet...

––This paper focuses on the needs of developing an automated Digital Library Management system .The purpose is to automate the task of analyzing data containing in raster image documents for the purpose of intelligent information retrieval in digital library. An efficient and computationally fast method for segmenting text and graphics part of document images based on multi-scale wavelet analysis and statistical pattern recognition is presented. The extracted text is further classified into Title, Author name, name of the publication etc and being stored in the database for further Library related operations. We do not assume any a priori information regarding the font size, scanning resolution, type of layout, etc. of the document in our segmentation scheme.

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001

In this paper, we present a novel method for processing double-sided historic handwritten documents using wavelets. The method is specially designed to remove the interfering strokes from the reverse side due to ink sipping through pages after long periods of storage. The proposed method works by first matching both sides of a document page such that the interfering strokes are mapped with the originating strokes from the reverse side. This is to facilitate the identification of the foreground and interfering strokes. A wavelet reconstruction process then iteratively enhances the foreground strokes and smears the interfering strokes so as to strengthen the discriminating capability of an edge detector to extract clear foreground image. This is an improvement of our earlier work.

Lecture Notes in Computer Science, 2001

The National Archives of Singapore keeps a large number of double-sided handwritten archival documents. Over long periods of storage, ink sipped through the pages of these documents, resulting in interfering images of handwriting coming from the back of the page. This paper addresses this problem of segmenting handwriting from both sides of a document by means of a wavelet approach. We first match both sides of a document page such that the interfering strokes are mapped with the corresponding strokes originating from the reverse side. This allows the identification of the foreground and interfering strokes. A wavelet reconstruction process then iteratively enhances the foreground strokes and smears the interfering strokes so as to strengthen the discriminating capability of an improved Canny edge detector against the interfering strokes. Experimental results confirm the validity of the wavelet approach. Fig. 6. One whole original page image and its final binarization results

Lecture Notes in Computer Science, 2013

Web pages consist of different visual segments, serving different purposes. Typical structural segments are header, right or left columns and main content. Segments can also have nested structure which means some segments may include other segments. Understanding these segments is important in properly displaying web pages for small screen devices and in alternative forms such as audio for screen reader users. There exist different techniques in identifying visual segments in a web page. One successful approach is Vision Based Segmentation Algorithm (VIPS Algorithm) which uses both the underlying source code and also the visual rendering of a web page. However, there are some limitations of this approach and this paper explains how we have extended and improved VIPS and built it in Java. We have also conducted some online user evaluations to investigate how people perceive the success of the segmentation approach and in which granularity they prefer to see a web page segmented. This paper presents the preliminary results which show that, people perceive segmentation with higher granularity as better segmentation regardless of the web page complexity.