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In this manuscript we recognize the handwritten Devnagari numerals. In our implementation we have used density and background directional distribution features for the zones, in which we divided the numeral samples already. We used the normalized images of samples of varying sizes of 32*32, 40*40 and 48*48. We divided these normalized images into 4*4 (16), 5*5 (25) and 6*6 (36) zones respectively...
This paper deals with the problem of recognizing accented and non-accented characters in French handwriting. Accented characters increase the number of classes to be recognized. The performances of powerful classifier such as SVM are declined by the presence of accents. In this paper, an accented character is segmented into two parts: the root character or letter and the accent. These two parts are...
A method for Off-line handwritten signature verification is described in this paper. Recently, several papers have proposed pseudo dynamic methods based on the ink deposition process to discriminate between genuine and fake signatures. The major problem of those methods is the ink texture normalization in order to make the system invariable to the pen. The more extreme pen normalization is the binarization...
In this paper, the local features obtained from the signature has been used to create the texture image based on the spatio-temporal correlation matrix. The Gabor wavelets exhibit desirable characteristics of spatial locality and orientation selectivity, and are optimally localized in the space and frequency domains. So it has been chosen to extract the Gabor features of the image. Signature is a...
Recently a new method for recognition of isolated handwritten Persian digits, based on support vector machines (SVMs), has been introduced. In this research, this method was implemented for the same task with three new modifications, i.e. only one popular shape was considered for digits written in different shapes; sizes of glyphs normalized to digit boundaries; MLP (multi-layer perceptron), SVM/MLP...
In this paper, we propose two types of feature sets based on modified chain-code direction frequencies in the contour pixels of input image and modified transition features (horizontally and vertically). A multi-level support vector machine (SVM) is proposed as classifier to recognize Persian isolated digits. In first level, we combine similar shaped numerals into a single group and as result; we...
In this paper we investigate the use of linguistic information given by language models to deal with word recognition errors on handwritten sentences. We focus especially on errors due to out-of-vocabulary (OOV) words. First, word posterior probabilities are computed and used to detect error hypotheses on output sentences. An SVM classifier allows these errors to be categorized according to defined...
Global features based on the boundary of a signature and its projections are described for enhancing the process of automated signature verification. The first global feature is derived from the total psilaenergypsila a writer uses to create their signature. The second feature employs information from the vertical and horizontal projections of a signature, focusing on the proportion of the distance...
As a kind of behavior-based personal identification techniques, automated Chinese handwriting identification becomes a hot topic in pattern recognition and machine learning research area. There are lots of key issues worthy researching. In this paper, the Chinese handwriting identification technology based on texture analysis is discussed. Firstly, a practical Chinese handwriting image samples library...
This paper presents a novel approach to recognize similar handwritten numerals based on empirical mode decomposition (EMD). We firstly use the local maximum modulus of wavelet transform (MMWT) to get the width-invariant and grey-level invariant characterization of contours in an image. Then we apply EMD analysis to decompose the synthetic shift normalization of curvature into their components, which...
Transforming handwriting into digital text and recognition of handwritten patterns opens a vast scope of application opportunities from searching for handwritten notes and document management to causing actions by writing symbols. Despite receiving a great attention, a massive number of applications, and a huge research effort, recognition of handwritten text has not still reached a desired efficiency...
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