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Character degradation is a major problem in character recognition. Most of the historical documents are degraded due to extrinsic factors like blurring, skew, background noise etc and intrinsic factors like distortion, broken characters, touching characters etc. In this paper we propose a novel approach of rebuilding the broken characters and then using neural network for recognition. Kannada characters...
A means to naturally recognizing and fetching out the content of video description would possibly make them indexed in considerable and appropriate way for later reference, and would facilitate actions viz. automatic notification and dissemination, to be triggered in real time by the contents of streaming video. Video text recognition, or video OCR, is a constructive tool to characterize the contents...
The most important necessity in image processing lies in the conversion of ancient Tamil characters to modern text. The ancient Tamil stone inscriptions are the source for these ancient Tamil characters. Analysing and Recognising the ancient Tamil characters from the scripts called inscriptions is a difficult task for the present generation who learn to educate, read and write only through the modern...
This work describes the development of online handwritten isolated Bengali numerals using Deep Autoencoder (DA) based on Multilayer perceptron (MLP) [1]. Autoencoders capture the class specific information and the deep version uses many hidden layers and a final classification layer to accomplish this. DA based on MLP uses the MLP training approach for its training. Different configurations of the...
A methodological study on significance of image processing and its applications in the field of computer vision is carried out here. During an image processing operation the input given is an image and its output is an enhanced high quality image as per the techniques used. Image processing usually referred as digital image processing, but optical and analog image processing also are possible. Our...
Selecting the parameters for the classification is a delicate process. We present in this paper a method for selecting the parameters by the genetic algorithm which optimizes the choice of parameters by minimizing a cost function. This function is defined by a Trace criterion. The approach is validated on some characters images. The proposed algorithm gives a fast convergence towards the optimal solution.
With the massive changes in input acquisition systems such as smart phones and tablets, the field of handwriting recognition has more attention accorded by a several researchers. This article addresses the problem of online Arabic character segmentation. Our approach is based on top-down segmentation-free of Arabic character by detecting the candidate points in the general chain code of the character...
The pattern recognition domain, particularly the online Arabic character recognition is a rich area of research. This paper puts forward a new approach for character recognition using domain ontology. Our main idea is based on the modeling of Arabic character by construction of ontology created by a domain expert. This ontology consists of a set of concepts and spatial relations between them. The...
There are several algorithms and methods that could be applied to perform the character recognition stage of an automatic number plate recognition system; however, the constraints of having a high recognition rate and real-time processing should be taken into consideration. In this paper four algorithms applied to Qatari number plates are presented and compared. The proposed algorithms are based on...
Vehicle number plate recognition (VNPR) is a technique used to extract the license plate from a sequence of images. The extracted information in the database can be used in the applications like electronic payment systems such as toll payment, parking lots etc. An effective VNPR can be implemented based on the quality of the acquired images. It is used for real time application and it has to recognize...
With the increasing number of shops and service providers offering loyalty cards and attractive benefits for card holders, the amount of different cards a typical customer owns has become a problem. In most cases, a card needs to be scanned in the particular shop to gain discounts meaning the customers have to always carry a large number of cards. In this paper, we present an approach to automatically...
There are a lot of difficulties facing a good handwritten Arabic recognition system such as the similarities of different character shapes and the unlimited variants in human handwriting. This paper presents a handwriting Arabic word recognition system. The objective of this approach is to propose an analytical offline recognition method of handwritten Arabic for rapid implementation. The first part...
Recognition of Arabic Character field has been gaining more interest for many years, and a large number of research papers and reports have already been published in this area. There are several major issues with Arabic character recognition: Arabic characters are spelled differently (depending on whether they are isolated, at the beginning, in the middle or at the end of the word), multiple characters...
In this paper, new methods were developed to successfully identify Chinese handwriting characters. These methods are based on features extraction as compared and matched with HCL2000 database [1]. Several algorithms were applied for binarization, smoothing, noise reduction and thinning to an image of a single Chinese character. Then the image is given to a structural feature extracting algorithm,...
Optical Character Recognition is one of the most important tools that contributes to facilitate man-machine interaction. In this paper, we present an optical Tifinagh character recognition system based on graph theory. After preprocessing, interest points are extracted using Harris corner detector. Based on these points, we constructed the graph model representation of Tifinagh characters. Classification...
Gesture identification plays a vital role in today's human-computer interaction. In this paper, we proposed a sensor based gesture recognition system which makes the teacher to write in Telugu language on digital board from anywhere within the class room. Various classification algorithms k-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Decision tree are individually used for hand gesture...
Immense analysis has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese, Devanagari, Malayalam, Arabic scripts, etc. Segmentation has imp phase in OCR and various articles have been published on different segmentation methods like Thinning, histogram etc for different script during last few years. Generally there is not work done on Overlapped and touching...
Hindi character recognition has been attempted by many, but recognition of only modifiers has not been attempted so far. In this paper we present an algorithm that recognizes modifiers independent of the main character. The algorithm is based on pixel relationship. The accuracy of modifier recognition based on this approach has been 87.78% which is far greater than 52% reported by previous work by...
The character recognition is an important issue, which has been pursued in recent year. In the paper, we used PCANet(principal component analysis network) to learn the character features. We verified the influence of these parameters on the performance of PCANet by modifying the key parameters of the experiment. Then we made a handwritten dataset to do the experiment and to verify whether the PCANet...
Text detection techniques assume that the frames given to them are all text frames. When a non-text frame is fed to the text detector there is an increase in the number of false positives which is a major issue in text detection and recognition. Hence, classification of text frames in a video sequence is important. The duplicate frames are eliminated and label each frame as text and non-text before...
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