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In this paper we present a novel writer-independent off-line signature verification system. This system utilises the discrete Radon transform and a dynamic time warping algorithm for writer-independent signature representation in dissimilarity space. The system also considers writer-specific statistics for dissimilarity normalisation. A discriminant function, either linear or quadratic, is utilised...
Handwritten Signatures are one of the widely used biometrics for document authentication as well as human authorization. The purpose of this paper is to present an off-line signature verification system involving Hindi signatures. Signature verification is a process by which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Despite...
We address, in this work, a new feature generation method for two different approaches of off-line handwritten signature verification (HSV), writer-dependent and writer-independent HSV. The proposed method uses conjointly the contourlet transform and the co-occurence matrix. The contourlet transform allows capturing contour segment directions of the handwritten signature, while the co-occurrence matrix...
Indicators of handwriting examination in recent forensic science are mainly figures on two dimensional planes. However forgeries of handwriting which are over-written on genuine one while being watched through paper aren't able to distinguish from the genuine one. This article tried to use other indicators with regard to pen-tip forces. Pen-tip forces were measured using a digitizer tablet during...
Due to the great variabilities in human writing, unconstrained handwriting recognition is still considered an open research topic. Recent trends in computer vision, however, suggest that there is still potential for better recognition by improving feature representations. In this paper we focus on feature learning by estimating and applying a statistical bag-of-features model. These models are successfully...
In recent years, many techniques for the recognition of Persian/Arabic handwritten documents have been proposed by researchers. To test the promises of different features extraction and classification methods and to provide a new benchmark for future research, in this paper a comparative study of Persian/Arabic handwritten character recognition using different feature sets and classifiers is presented...
Urdu being one of the most popular languages adopted during different swatches of history has a valuable collection of handwritten scripts in different state libraries of South Asia. Digitizing these collections can serve not only to preserve them but also to make them available to general public. Non existence of an Urdu OCR, however, limits the concept of a digital Urdu library to scanning and manual...
In this paper we present the importance of including the user in the loop in a handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and a baseline word...
Tabular structure detection and recognition can be a valuable step in the analysis of unstructured documents. The noisy handwritten documents we try to analyze may contain pre-printed rulings as the substrate, hand-drawn rulings, machine-printed text, handwritten text, and signatures, in addition to the tabular structures which we wish to decompose into basic cells, rows, and columns. Although work...
This paper presents a new offline dataset called the Qatar University Writer Identification dataset (QUWI). This dataset contains both Arabic and English handwritings and can be used to evaluate the performance of offline writer identification systems. It consists of handwritten documents of 1017 volunteers of different ages, nationalities, genders and education levels. The writers were asked to copy...
A novel approach to the problem of keyword retrieval in cursive handwritten documents is introduced in this work. Two issues are addressed: small dataset size and uneven sample distribution across the character set. The proposed strategies utilise graphemes (fragments of a handwritten word) to implement a recognition model which is subsequently used to form the feature model for the query word.
In this paper, we present a complete courtesy amount recognition system for Chinese bank checks. The system takes color bank check images as input and consists of three main processing steps: numeral string extraction, segmentation & recognition, and post-processing. They focus sequentially on: detection and extraction of numeral string; segmentation and recognition of the string; and further...
This paper presents a new component-based recognition method using conditional random field (CRF) for on-line handwritten Tibetan characters. The character pattern is over-segmented into a sequence of sub-structure blocks. Integrated segmentation and recognition method based on the CRF model is used to determine the component segmentation points from these block sequences. The CRF model combines component...
The training of most of the existing recognition systems requires availability of large datasets labeled at the symbol level. However, producing ground-truth datasets is a tedious work. Two repetitive tasks have to be chained. One is to select a subset of strokes that belong to the same symbol, a next step is to assign a label to this stroke group. In this paper, we discuss a framework to reduce the...
Under three-language formula, the destination address block of postal document of an Indian state is generally written in three languages: English, Hindi and the State official language. From the statistical analysis we found that 12.37%, 76.32% and 10.21% postal documents are written in Bangla, English and Devanagari script, respectively. Because of inter-mixing of these scripts in postal address...
Because of the existence of possible carbon and seals, it's quite often that images of financial documents such as Chinese bank checks are suffered from bleed-through effects, which will affect the performance of automatic financial document processing such as seal verification and OCR. This paper presents an effective algorithm to deal with bleed-through effects existing in the images of financial...
Feature extraction is an important step in off-line handwriting recognition systems to represent raw handwriting in a low-dimensional, tractable feature space. Traditionally, linear feature transforms such as Principle Component Analysis (PCA), Linear Discriminative Analysis (LDA) are commonly used. The assumptions they make, however, usually cannot be satisfied in practice and thus the best performance...
This paper presents a novel segmentation-based and lexicon-driven handwritten English recognition systems. For the segmentation, a modified online segmentation method based on rules are applied. Then, convolutional neural networks are introduced for offline character recognition. Experiments are evaluated on UNIPEN lowercase data sets, with the word recognition rate of 92.20%.
The main goal of this work is to set up a multimodal system dedicated to mathematical expression recognition. In the proposed architecture, the transcription coming out from a speech recognition system is used to disambiguate the result of a handwriting recognition module. A set of keywords is built from the transcription module and used to rescore the outputs of both the handwriting classifier and...
We present a system for recognizing online mathematical expressions (ME). Symbol recognition is based on a template elastic matching distance between pen direction features. The structural analysis of the ME is based on extracting the baseline of the ME and then classifying symbols into levels above and below the baseline. The symbols are then sequentially analyzed using six spatial relations and...
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