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Handwritten signature datasets are really necessary for the purpose of developing and training automatic signature verification systems. It is desired that all samples in a signature dataset should exhibit both inter-personal and intra-personal variability. A possibility to model this reality seems to be obtained through the synthesis of signatures. In this paper we propose a method based on motor...
This paper presents a study of line-wise text identification in comic books. Due to the unavailability of a single OCR system which can handle comic text of multiple scripts, the comic text identification based on script becomes an essential step for choosing the appropriate OCR. In this investigation, a new attempt has been made to explore a comic text identification technique of speech balloon to...
In this paper, we have presented a new and faster word retrieval approach, which is able to deal with heterogeneous document image collections. A certain amount of image features (statistical and Gabor Wavelet) are extracted, which inherently represent word's images. These features are used for generating hash table for fast retrieval of similar image from a very large image dataset. The decomposition...
Script identification is an important step in multi-script document analysis. As different textures present in text portion of a script are the main distinct features of the script, in this paper, we proposed a new algorithm for printed script identification based on texture analysis. Since local patterns is a unifying concept for traditional statistical and structural approaches of texture analysis,...
In this paper, we address the issues pertaining to segmentation and recognition of cursive handwritten text from chalkboard lecture videos. Recognizing handwritten text is a challenging problem in instructor-led lecture video. The task gets even tougher with varying handwriting styles and blackboard type. Unlike handwritten text on whiteboard and electronic boards, chalkboard represents serious challenges...
This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is...
Biometric systems play an important role in the field of information security as they are extremely required for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is currently receiving renewed interest and is only one of several techniques used to verify the identities of individuals. Signatures provide a secure means for confirmation...
A dataset containing 26,720 handwritten legal amount words written in Hindi and Marathi languages (Devanagari script) is presented in this paper along with a training-free technique to recognize such handwritten legal amounts present on Indian bank cheques. The recognition of handwritten legal amount words in Hindi and Marathi languages is a challenging because of the similar size and shape of many...
Research towards Indian handwritten document analysis achieved increasing attention in recent years. In pattern recognition and especially in handwritten document recognition, standard databases play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. For Indian languages, there is a lack of standard database of handwritten texts...
In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can be efficiently represented by graphs, which ease the accurate localization of the model symbol. Graph paths are the factorized substructures of graphs which enable robust recognition even in the presence of noise and distortion...
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