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Digitization of documents has gained prominence in the recent past for data preserving. Paper documents can be converted to digital form by using various modes of acquisition techniques. In this paper processing of data captured using normal digital camera has been considered. The camera captured document images may contain warped document due to perspective and geometric distortions. Curvature of...
This article presents our recent study on multi colored text binarization. In the output image, we represented foreground content as black and background as white regardless the polarity of foreground and background in original image. Here we applied connected component analysis based approach to group the words or characters within bounding or edge box. The main novelty of this reported work includes...
Document layout helps users to focus on important content of the documents while neglecting the rest whenever possible. This paper presents a novel Optical Character Recognition (OCR) algorithm whose performance is enhanced by post-processing based on information collected from document layout analysis. Initial OCR results are used for text block classification, whose results are then used to fine-tune...
In this paper, we are proposing a new semantic and contextual based document image classification framework. The framework is composed of two main modules. The first one is the text analysis module (TAM) which processes document images and extracts words from the image, and second one is the SEMCON, which is a semantic and contextual objective metric. From the list of extracted words by TAM, SEMCON...
In this paper, we present a hybrid method consisting of three main stages for detecting tables in document images. Based on table structure, our system separates table into two main categories, ruling line table and non-ruling line table. In the first stage, the text and non-text elements in document are classified by a heuristic filter. Then, the white space analysis is used to group the text elements...
Script identification has long been the forerunner of many Optical Character Recognition (OCR) processes in a multi-lingual document environment. Script identification has numerous applications in the field of document image analysis, such as document sorting, indexing, retrieval and translation, etc. In this paper, we have developed a page-level script identification technique for handwritten documents...
The state-of-arts global thresholding techniques are fast and efficient to convert the gray scale document image into a binary image. However, they are unsuitable for complex and degraded documents. Moreover, global thresholding techniques produce border noise when the illumination of the document is not uniform. Other methods that depend on local thresholding techniques are efficient in the case...
Text extraction plays an important role in numerous applications. Research on its method still need to be improved in order to achieve better performance, to increase the reliability of text extraction system and to deal with complex cases of text extraction. The majority of the text extraction methods are focusing on horizontal and near horizontal text lines; however, text in natural scene might...
The document layout analysis is a complex task in the context of heterogeneous documents. It is still a challenging problem. In this paper, we present our contribution for the layout analysis competition of the international Maurdor Campaign. Our method is based on a grammatical description of the content of elements. It consists in iteratively finding and then removing the most structuring elements...
In this paper we describe the undertaking of a quantitative, historically oriented analysis of the law of England between 1650–1700 as represented in Howell's State Trials. Our goal was to analyze cases over time to support investigation into whether a quantitative analysis of the content of the 1650–1700 State Trials would exhibit an upward trend of religious tolerance.
Online educational lecture videos are very popular nowadays. However, effective search of relevant videos remains a difficult task. Texts displayed in lecture video slides have important information about the video content. Therefore, it can be utilized as a valuable source of content analysis and tagging. In this paper, we present an automated method for semantic segmentation and tag recommendation...
Nowadays, Document forgery detection is becoming increasingly important as forgery techniques are becoming available even to untrained users. Hence, documents that do not contain any extrinsic security features (e.g. invoices) have become easier to forge. We previously presented a method to detect manipulated documents based on distortions introduced during the forgery creation process. In this paper,...
In this study, two different Ottoman and Turkish handwritten recognition systems have been developed using Hidden Markov Model (HMM) and Recurrent Neural Network (RNN). The systems are tested in both public use datasets and Civil Registration and Nationality (CRN) dataset. As public use datasets, IFN/ENIT dataset which is created for Arabic language, is used because of the similarity between Ottoman...
From a single low resolution image, a real-time document image super-resolution algorithm is proposed to obtain high resolution document image with sharp text boundaries. First, a highly efficient document image matting algorithm based on local linear modeling is designed to decompose the input image into text, foreground and background layers, which contain the text edge information, the color information...
Detection and analysis of tables on document images has been one of the most researched topics in document image processing. In this study, we define novel methods for the detection and analysis of tables from document images, and show their performance results on realistic table examples. The main method developed is projection-scale-space (PSS), where local and global constraints of the table in...
In this paper we propose a neural net based characters recognition scheme for Bangla printed text books. There are a lot of scientific literature, novels, magazines and books etc that are written in Bangla language. More than 400 million people use Bangla language. Most of the library and educational institutions want to keep copy of the books in a digital format. For storing those books in digital...
A document image contains texts and non-texts, it may be printed, handwritten, or hybrid of both. In this paper we deal with printed document where textual region is of printed characters, and non-texts are mainly photo images. Here we propose a model which performs labeling of different components of a printed document image, i.e. identification of heading, subheading, caption, article and photo...
Document layout analysis is necessary process for automated document recognition systems. Document layout analysis identifies, categorizes and labels the semantics of text blocks for meaningful information retrieval from document images. Our primary target document includes various newspaper and magazine pages which are having complex layout without following any static rules. We propose an effective...
Reading order detection and representation is an important task in many digitisation scenarios involving the preservation of the logical structure of a document. The corresponding need for the evaluation of reading order results generated by layout analysis methods poses a particular challenge due to potential deviations between ground truth and actually detected segmentation of the page. To this...
We present a novel binarization method that is especially effective on historical documents with the following characteristics: (a) the documents contain free-form cursive handwritten text with significant but consistent slant, (b) scanning artifacts resulting in the text and background pixels not having uniform intensity even within the same page, and (c) pages containing significant amount of bleeds...
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