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We present the outcome of the latest edition of the CROHME competition, dedicated to on-line handwritten mathematical expression recognition. In addition to the standard full expression recognition task from previous competitions, CROHME 2014 features two new tasks. The first is dedicated to isolated symbol recognition including a reject option for invalid symbol hypotheses, and the second concerns...
We discuss in this paper some issues related to the problem of mathematical expression recognition. The very first important issue is to define how to ground truth a dataset of handwritten mathematical expressions, and next we have to face the problem of benchmarking systems. We propose to define some indicators and the way to compute them so as they reflect the actual performances of a given system.
An unconstrained online handwritten Chinese text lines dataset, SCUT-COUCH Textline_NU, a subset of SCUT-COUCH [1] [2], is built to facilitate the research of unconstrained online Chinese text recognition. Texts for hand copying are sampled from China Daily corpus with a stratified random manner. The current vision of SCUT-COUCH Textline_NU has 8,809 text lines (4,813 lines are collected by touch...
We propose in this paper a new contextual modelling method for combining syntactic and structural information for the recognition of online handwritten mathematical expressions. Those models are used to find the most likely combination of segmentation/recognition hypotheses proposed by a 2D segment or. Models are based on structural information concerning the layouts of symbols. They are learned from...
In this paper, we propose a new framework for online handwritten mathematical expression recognition. The proposed architecture aims at handling mathematical expression recognition as a simultaneous optimization of symbol segmentation, symbol recognition, and 2D structure recognition under the restriction of a mathematical expression grammar. To achieve this goal, we consider a hypothesis generation...
Script identification has always been a topic of much research interest in the field of document analysis. The accurate determination of the identity of the script is paramount to many post-processing steps such as document sorting, translation and in determining the choice of linguistic resources to use for OCR or handwriting recognition. However, few works exist with regards to the identification...
Hybrid of neural network (NN) and hidden Markov model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capability. However, NN does not guarantee good generalization due to empirical risk minimization (ERM) principle that it uses. In our work, we focus on using the support vector machine (SVM) for character recognition. SVM's use of...
Character prototype approaches for writer identification produces a consistent set of templates that are used to model the handwriting styles of writers, thereby allowing high accuracies to be attained. This paper extends such work on writer identification by investigating the usage of alphabet knowledge derived from the character prototypes. In addition, we demonstrate the concept of discriminative...
The traditional weighting schemes used in text categorization for the vector space model (VSM) cannot exploit information intrinsic to texts obtained through online handwriting recognition or any OCR process. Especially, top n (n > 1) recognition candidates could not be used without flooding the resulting text with false occurrences of spurious terms. In this paper, an improved weighting scheme...
In this paper we experiment the capabilities of Hidden Markov Models (HMM) to model the time-variant signal produced by the movement of a pen when drawing a sketch such as an electrical circuit diagram. We consider that the sketches have been generated by a two-level stochastic process. The underlying process governs the stroke production from a neuro-motor control point of view: go straight, change...
One novel technique for identifying the writer of an online handwritten document is proposed. This technique makes use of a character prototype distribution to model the specific allographs used by a given writer. In this paper, we propose to extend and improve upon this newly established methodology by S.K. Chan et al (2008) by making use of a stochastic nearest neighbor algorithm to estimate the...
With the growth of on-line handwriting technologies, managing facilities for handwritten documents, such as retrieval of documents by topic, are required. These documents can contain graphics, equations or text for instance. This work reports experiments on categorization of on-line handwritten documents based on their textual contents. We assume that handwritten text blocks have been extracted from...
Recently, with the advances in digital pen and paper technology, renewed attention was given on research for writer identification of online documents. This paper proposes a method to retrieve the writer of a document by comparing his handwriting with those stored in a reference database of documents. The query will consist of a testing online handwriting document, the output will be a ranked list...
Handwriting is an alternative method for entering texts composing short message services. However, a whole new language features the texts which are produced. They include for instance abbreviations and other consonantal writing which sprung up for time saving and fashion. We have collected and processed a significant number of such handwriting SMS, and used various strategies to tackle this challenging...
This paper describes an application of neural networks in the field of objective measurement method designed to automatically assess the perceived quality of digital videos. This challenging issue aims to emulate human judgment and to replace very complex and time consuming subjective quality assessment. Several metrics have been proposed in literature to tackle this issue. They are based on a general...
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