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Accurate character recognition is still very important for camera based printed document analysis. Due to its inherent conceptual and technical simplicity, conventional recognition strategies relied on features extracted using square block zoning of a character image. In this paper, we propose an isotropic feature extraction method using regular hexagonal zoning and confirm its effectiveness by printed...
This paper addresses the problem of holistic recognition of printed ligatures in Nastalique writing style of the Urdu language. The main difficulty of the recognition process lies in the large number of classes/ligatures (17,000 different possible ligatures in our Urdu text data). This large number of classes not only limits the efficiency (run-time) of the recognition algorithms, but also makes it...
The task of classifying mixed Thai-English characters carries considerable challenges due to the number and complexity of the characters. This paper proposes and empirically investigates the performance of a classification system that uses Histogram of Oriented Gradient as an image feature with Support Vector Machine as a classification tool. The experiments were done on the datasets provided by NECTEC...
This paper examines the problem of decoding a unique CAPTCHA that has very high noise levels with only partially visible symbols with variable spacing but no skewing. An ingenious method for decoding is proposed that starts with preprocessing the image and identifies symbols first before removing them from the image, unlike a number of existing methods. The algorithm is expected to be very fast owing...
This paper addresses the problem of recognizing rotated characters in scene and estimating the rotation angle using Weighted Direction Code Histogram (WDCH) and Modified Quadratic Discriminant Function (MQDF). In our previous paper [1], we proposed a rotation-free character recognition method and confirmed the feasibility of real world application. We also applied our method to scene analysis to detect...
Present a novel method of character stroke feature extraction based on the histogram of gradient angles. Firstly, produce the gradient angle matrix of the pixels in the character edge by sifting out the gray image using the SOBEL operator. Secondly, set up the character stroke features as sub-vectors of each block matrix using the relationship between the gradient angle matrix and the character strokes...
The paper presents a method for isolated off-line character recognition using radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of radon histograms at every projecting angle. Thanks to DTW, it avoids compressing feature matrix into a single vector which may miss information. Comparison has been made with the state-of-the-art of shape descriptors...
In this paper, we present a novel method to recognize characters with severe perspective distortion using hash tables and perspective invariants. The proposed algorithm consists of storage and voting stages. With the help of perspective invariants, the combinations of 4-tuple bases for the perspective invariant coordinate system are searched out in an efficiently way. The bases are further selected...
This paper describes a method of identifying authorship of Ukiyoe prints by using Rakkan images found in the prints. A weighted direction index histogram method has been used to create the feature vector for Rakkan character analysis. Also the Pseudo Mahalanobis distances were used to judge distances between dictionary templates and test data. The method includes binarization of Rakkan images which...
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