A CRF Based Scheme for Overlapping Multi-colored Text Graphics Separation
18 Sep 2011-pp 1215-1219
TL;DR: A novel framework for segmentation of documents with complex layouts performed by combination of clustering and conditional random fields (CRF) based modeling and has been extensively tested on multi-colored document images with text overlapping graphics/image.
Abstract: In this paper, we propose a novel framework for segmentation of documents with complex layouts. The document segmentation is performed by combination of clustering and conditional random fields (CRF) based modeling. The bottom-up approach for segmentation assigns each pixel to a cluster plane based on color intensity. A CRF based discriminative model is learned to extract the local neighborhood information in different cluster/color planes. The final category assignment is done by a top-level CRF based on the semantic correlation learned across clusters. The proposed framework has been extensively tested on multi-colored document images with text overlapping graphics/image.
Citations
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TL;DR: This survey highlights the variety of the approaches that have been proposed for document image segmentation since 2008 and provides a clear typology of documents and of document images segmentation algorithms.
Abstract: In document image analysis, segmentation is the task that identifies the regions of a document. The increasing number of applications of document analysis requires a good knowledge of the available technologies. This survey highlights the variety of the approaches that have been proposed for document image segmentation since 2008. It provides a clear typology of documents and of document image segmentation algorithms. We also discuss the technical limitations of these algorithms, the way they are evaluated and the general trends of the community.
84 citations
Cites background from "A CRF Based Scheme for Overlapping ..."
...[110] separate text and graphics in challenging magazine covers....
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...Algorithm Input layout Multilayered Color depth Labels Training Type of output Text orientation Text alignment Data set test size Nb of languages Nb of doc types [72] Any Yes Color Yes No Text lines Horizontal Straight 448 1 2 [104] Any Yes Color Yes Yes Regions Any Curved 87 1 2 [110] Any Yes Color Yes Yes Regions Any Curved 16 2 1 [51] Any Yes Color No No Regions Any Curved 2000 2 2 [74] Any Yes Color No No Text lines Any Curved 50 1 1 [84] Any Yes Color No Yes Text lines Any Straight 21 2 1 [54] Any Yes Gray Yes No Regions Horizontal Straight 65 2 1 [112] Any Yes BW Yes Yes Regions Horizontal Straight 1000 3 6 [89] Any No Color Yes Yes Regions Any Curved 100 1 1 Continued on next page...
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09 Sep 2013
TL;DR: This paper tries to find a new way which can utilize existing methods to detect and extract text from born-digital image.
Abstract: The text appears in the images is important for fully understanding the images. The number of digital images and digital videos has increased tremendously. Although there are many methods have been proposed over the past years for the text extraction from natural scene images, the text detection and extraction from born-digital images are still a challenge. In this paper, we describe existing methods key ideas and try to summarize their advantages and disadvantages. We try to find a new way which can Comprehensive utilize existing methods to detect and extract text from born-digital image.
12 citations
Cites methods from "A CRF Based Scheme for Overlapping ..."
...1) Method based on CC [2-15] The method consists of two steps....
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10 Dec 2013
TL;DR: An approach to separate the non-texts from texts of a manuscript, mainly in the form of doodles and drawings of some exceptional thinkers and writers, and a computational approach to recover the struck-out texts to reduce human effort.
Abstract: In this paper we propose an approach to separate the non-texts from texts of a manuscript. The non-texts are mainly in the form of doodles and drawings of some exceptional thinkers and writers. These have enormous historical values due to study on those writers’ subconscious as well as productive mind. We also propose a computational approach to recover the struck-out texts to reduce human effort. The proposed technique has a preprocessing stage, which removes noise using median filter and segments object region using fuzzy c-means clustering. Now connected component analysis finds the major portions of non-texts, and window examination eliminates the partially attached texts. The struck-out texts are extracted by eliminating straight lines, measuring degree of continuity, using some morphological operations.
10 citations
Cites methods from "A CRF Based Scheme for Overlapping ..."
...The existing methods [2-10] deal with different logos, diagrams, maps, engineering drawings and photographic images....
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TL;DR: A consensus-based clustering approach for document image segmentation that is used iteratively with a classifier to label each primitive block and shows that the dependency of classification performance on the training data is significantly reduced.
Abstract: Segmentation of a document image plays an important role in automatic document processing. In this paper, we propose a consensus-based clustering approach for document image segmentation. In this method, the foreground regions of a document image are grouped into a set of primitive blocks, and a set of features is extracted from them. Similarities among the blocks are computed on each feature using a hypothesis test-based similarity measure. Based on the consensus of these similarities, clustering is performed on the primitive blocks. This clustering approach is used iteratively with a classifier to label each primitive block. Experimental results show the effectiveness of the proposed method. It is further shown in the experimental results that the dependency of classification performance on the training data is significantly reduced.
9 citations
Cites methods from "A CRF Based Scheme for Overlapping ..."
...A bottom-up approach using conditional random field (CRF) for text–graphics separation has been reported in [21]....
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01 Feb 2017
TL;DR: STRHOG, an extended version of HOG that is helpful for filtering spam images on cloud and a fair comparison with other methods, nearest neighbor classifier is used for the intelligent character recognition.
Abstract: Cloud storage has become an important way for data sharing in recent years. Data protection for data owner and harmful data filtering for data recipients are two non-negligible problems in cloud storage. Illegal or unsuitable messages on cloud have a negative impact on minors and they are easily converted into images to avoid text-based filtering. To detect the spam image with the embedded harmful messages on cloud, soft computing methods are required for intelligent character recognition. HOG, proposed by Dalal and Triggs, has been demonstrated so far to be one of the best features for intelligent character recognition. A pre-defined sliding window is always used for the generation of candidate character images when HOG is applied to recognize the whole word. However, due to the difference in character sizes, the pre-defined window cannot exactly match with each character. Variations on scale and translation usually occur in the character image to be recognized, which have a great influence on the performance of intelligent character recognition. Aiming to solve this problem, STRHOG, an extended version of HOG, is proposed in this paper. Experiments on two public datasets and one our dataset have shown encouraging results for our work. The improved intelligent character recognition is helpful for filtering spam images on cloud. To make a fair comparison with other methods, nearest neighbor classifier is used for the intelligent character recognition. It is expected that the performance should be further improved by using better classifiers such as fuzzy neural network.
7 citations
References
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03 Sep 2000
TL;DR: This paper addresses the layout analysis of complex documents and addresses the knowledge representation of layout structure, which is based on operator-specification.
Abstract: Many methods for understanding document images have been investigated to extract/classify meaningful information from paper-based documents. These methods focused on the same types/classes of documents whose layout structures can be represented by single specification. However, widely used documents are not always simple, but composed of different types/classes of simple ones: these documents cannot be represented by a simple document model. In this paper, we address the layout analysis of complex documents. In particular, the knowledge representation of layout structure is discussed. Although the representation means are divided into structure description and operator-specification, our representation means is based on operator-specification.
10 citations
"A CRF Based Scheme for Overlapping ..." refers background in this paper
...Many model-guided segmentation and layout analysis schemes [6], [7] are also reported in literature....
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Journal Article•
TL;DR: A new approach to segment documents with complex layout and degraded image quality is described which uses a local-to-global strategy which can be adapted to a variety of documents.
Abstract: Document layout analysis is concerned about the decomposition of raster representation of a document into several regions which contain homogeneous entities. This paper describes a new approach to segment documents with complex layout and degraded image quality. The approach uses a local-to-global strategy which can be adapted to a variety of documents. The system was tested on different English and Japanese documents and the experiments had shown promising results.
4 citations
"A CRF Based Scheme for Overlapping ..." refers methods in this paper
...Approach proposed in [3] uses a combination of top-down and bottom-up methodology for handling documents with complex layouts....
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25 Jul 2009
TL;DR: A framework for classification of text document images based on their script and uses edge direction based features to capture the distribution of curvature and a recently proposed feature selection algorithm to obtain the most discriminating curvature features.
Abstract: We present a framework for classification of text document images based on their script. We deal with the domain of Indian scripts which has high inter script similarities. Indian scripts have characteristic curvature distributions which help in visual discrimination of scripts. We use edge direction based features to capture the distribution of curvature. We also use a recently proposed feature selection algorithm to obtain the most discriminating curvature features. We form hierarchy (automatically) based on statistical distances between the script models. Hierarchy allows us to group similar scripts at one level and then focus on the classification between the similar scripts at the next level leading to improvement in accuracy. We show experiments and results on a large set of about 3400 images.
4 citations
01 Sep 2001
TL;DR: A prototype form extraction system that utilises colour information to help facilitate data extraction from a form using techniques based upon the colour characteristic changes that have occurred with respect to the blank form is described.
Abstract: Colour has long been viewed as one of the unnecessary features in any form processing system, due not only to the large storage requirement and computational cost its inclusion imposes but also to the complexities of hue, chroma and brightness variation However, as technology has advanced and computing costs have reduced, the processing of documents in colour has now become practical This paper describes a prototype form extraction system that utilises colour information to help facilitate data extraction from a form Blank forms are first automatically analysed to obtain their layout, colour and statistical information The filled data is then extracted from the filled forms using techniques based upon the colour characteristic changes that have occurred with respect to the blank form The improved performance of the proposed method has been verified by comparing the processing time, data extraction precision and recall rate of the proposed system to that of an archetypal black and white form extraction system
3 citations
"A CRF Based Scheme for Overlapping ..." refers methods in this paper
...Layout analysis using color information have been proposed in [9]–[11] to handle color document images with complex layouts such as forms, text overlaid on image, posters etc....
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18 Sep 2003
TL;DR: A new method is proposed to automatically detect and extract text in mixed type color documents based on a combination of an adaptive color reduction (ACR) technique and a page layout analysis (PLA) approach.
Abstract: In complex color documents, text, drawings and graphics are appeared with millions of different colors. In many cases, text regions are overlaid onto drawings or graphics. In this paper, a new method is proposed to automatically detect and extract text in mixed type color documents. The proposed method is based on a combination of an adaptive color reduction (ACR) technique and a page layout analysis (PLA) approach. The ACR technique is used to obtain the optimal number of colors. Then, image is split to separable binary images, each one corresponding to every principal color. The PLA technique is applied independently to each one of the color plains and identifies the text regions. A merging procedure is applied in the final stage to merge the text regions derived from the color plains and to produce the final document.
2 citations