There are many scripts in the world, several of which are used by hundreds of millions of people. Handwritten character recognition studies of several of these scripts are found in the literature. Different hand-craft...
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ISBN:
(纸本)9781479918065
There are many scripts in the world, several of which are used by hundreds of millions of people. Handwritten character recognition studies of several of these scripts are found in the literature. Different hand-crafted feature sets have been used in these recognition studies. However, convolutional neural network (CNN) has recently been used as an efficient unsupervised feature vector extractor. Although such a network can be used as a unified framework for both feature extraction and classification, it is more efficient as a feature extractor than as a classifier. In the present study, we performed certain amount of training of a 5-layer CNN for a moderately large class character recognition problem. We used this CNN trained for a larger class recognition problem towards feature extraction of samples of several smaller class recognition problems. In each case, a distinct Support Vector Machine (SVM) was used as the corresponding classifier. In particular, the CNN of the present study is trained using samples of a standard 50-class Bangla basic character database and features have been extracted for 5 different 10-class numeral recognition problems of English, Devanagari, Bangla, Telugu and Oriya each of which is an official Indian script. recognition accuracies are comparable with the state-of-the-art.
Air-writing refers to virtually writing linguistic characters through hand gestures in three dimensional space with six degrees of freedom. In this paper a generic video camera dependent convolutional neural network (...
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Air-writing refers to virtually writing linguistic characters through hand gestures in three dimensional space with six degrees of freedom. In this paper a generic video camera dependent convolutional neural network (CNN) based air-writing framework has been proposed. Gestures are performed using a marker of fixed color in front of a generic video camera followed by color based segmentation to identify the marker and track the trajectory of marker tip. A pre-trained CNN is then used to classify the gesture. The recognition accuracy is further improved using transfer learning with the newly acquired data. The performance of the system varies greatly on the illumination condition due to color based segmentation. In a less fluctuating illumination condition the system is able to recognize isolated unistroke numerals of multiple languages. The proposed framework achieved 97.7%, 95.4% and 93.7% recognition rate in person independent evaluation over English, Bengali and Devanagari numerals, respectively.
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...
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The digital camera captured document images may often be warped and distorted due to different camera angles or document surfaces. A robust technique is needed to solve this kind of distortion. The research on dewarpi...
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In this paper we present an invisible spatial domain watermarking technique. The technique divides the image into n small blocks and the intensity of some of these blocks are modified depending on the key, which is a ...
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To date, identifying cracks in bridges and determining bridge conditions primarily involve manual labour. Bridge inspection by human experts has some drawbacks such as the inability to physically examine all parts of ...
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To make predictions on unseen classes, few-shot segmentation becomes a research focus recently. However, most methods build on pixel-level annotation requiring quantity of manual work. Moreover, inherent information o...
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In this paper we provide a cryptanalysis of the well known "Optimal Differential Energy Watermarking (DEW)" scheme. The DEW scheme divides the image into some disjoint regions (each region containing two sub...
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We summarize the tasks, protocol, and outcome for the 6th Competition on recognition of Handwritten Mathematical Expressions (CROHME), which includes a new formula detection in document images task (+ TFD). For CROHME...
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In this piece of work a wrist vein patternrecognition and verification system is proposed. Here the wrist vein images from the PUT database were used, which were acquired in visible spectrum. The vein image only high...
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