The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a methodology for recognition of handwritten Marathi and English Characters-Numerals using shape context descriptor. During pre-processing an algorithm is developed to extract the Marathi and English Characters-Numerals form grid formatted datasheets. The corresponding sample points around the boundary of a character are computed. This is followed by obtaining the centroid of the...
This paper proposes a model for an offline handwritten Khmer character recognition. We make use of two dimensional Fourier transformation for feature selection and feed-forward Artificial Neural Net as classification tool. The recognition system allows using the nature of Khmer writing, which is an example of alphasyllabary (Abugida) writing systems. The recognition of the normalized handwritten images...
Trademark retrieval systems have been a well researched field however majority of these researches have been done on device trademarks and do not consider the presence of text embedded within trademark images as in case of composite marks. In this work a unified retrieval system has been proposed and implemented for composite trademarks. The technique is invariant to font size, font style and orientations,...
Devanagari is an alphabetic script which is used by different Indian languages such as Marathi, Hindi, Konkani and Nepali. This script consists of 13 vowels, 34 consonants and 10 numerals. Due to unconstrained shape and variation in writing style, recognizing such handwritten script is challenging task. This paper proposed a system for recognizing handwritten numerals and vowels of Devanagari Script...
Automatic character recognition of handwritten numerals and characters has been an active subject of research due to its importance on industrial as well as educational platform. The off-line handwritten character recognition is an active area for research towards the new techniques that would help to improve recognition accuracy. Now a day's looking forward for rapidly growing technologies, with...
Modi was very useful script in the kingdoms of medieval Maharashtra. In the reign of the great Maratha-Chhatrapati Shivaji and also in the reign of Peshwas, this script was widely incorporated in ruling the state. This script is very similar to the shorthand. At that time, it was used in Maharashtra to prepare the documents such as Property matters, Donation of Land (Dan-Patra), Land Revenue, Military...
The Project is based on design & implementation of smart hybrid system for street sign boards recognition, text and speech conversions through character extraction and symbol matching. The default language use to pronounce signs on the street boards is English. Here we are proposing a novel method to convert identified character or symbol into multiple languages like Hindi, Marathi, Gujarati,...
Recognizing offline handwritten Telugu characters from digitized document images is very challenging. In this paper, we propose a novel approach of hybrid feature extraction and hierarchical classification to recognize the glyphs of offline handwritten Telugu characters. In the proposed method, hybrid features are extracted from the glyphs and the glyphs are recognized using a hierarchical classification...
In this paper, we propose a technique for retrieval of printed Kannada words from a digital repository based on Gabor wavelets and structural features. Gabor wavelets are employed to capture global properties of the underlying image whereas structural features are used to extract the local properties. We call the combination of these features as Glocal. An input document image is segmented into words...
For development of offline Handwritten Character Recognition (HWCR) system, scripts have always posed a difficulty. In the proposed system, we present neural and non-neural approach for classification of different characters. After pre-processing, features are extracted using Chain code histogram and Intersection junction techniques. BPN, KNN & SVM have been used to train and classify the Devnagari...
With the rapid increase of multimedia data, textual content in an image has become a very important source of information for several applications like navigation, image search and retrieval, image understanding, captioning, machine translation and several others. Scene text localization is the first step towards such applications and most current methods focus on generating a small set of high precision...
This paper proposes a novel segmentation-free approach using deep neural network based hidden Markov model (DNN-HMM) for offline handwritten Chinese text recognition. In the general Bayesian framework, three key issues are comprehensively investigated, namely feature extraction, character modeling, and language modeling. First, as for the feature extraction on the basis of each frame or sliding window,...
The complexity of Balinese script and the poor quality of palm leaf manuscripts provide a new challenge for testing and evaluation of robustness of feature extraction methods for character recognition. With the aim of finding the combination of feature extraction methods for character recognition of Balinese script, we present, in this paper, our experimental study on feature extraction methods for...
The path signature feature (PSF) which was initially introduced in rough paths theory as a branch of stochastic analysis, has recently been successfully applied to the field of pattern recognition for extracting sufficient quantity of information contained in a finite trajectory, but with potentially high dimension. In this paper, we propose a variation of path signature representation, namely the...
Most research in image classification has focused on applications such as face, object, scene and character recognition. This paper examines a comparative study between deep convolutional neural networks (CNNs) and bag of visual words (BOW) variants for recognizing animals. We developed two variants of the bag of visual words (BOW and HOG-BOW) and examine the use of gray and color information as well...
License Plate Recognition System (LPRS) plays a vital role in smart city initiatives such as traffic control, smart parking, toll management and security. In this article, a cloud-based LPRS is addressed in the context of efficiency where accuracy and speed of processing plays a critical role towards its success. Signature-based features technique as a deep convolutional neural network in a cloud...
This paper focuses in particular on the problem of Chinese characters recognition in natural scenes. Due to large variation in fonts, sizes, illumination, cluttered backgrounds, geometric distortions, etc., scene text recognition in the wild is a challenging problem. We proposed a novel method which based on Integral Channel Feature and pooling technology to extract informative features from scenes...
Fourier descriptors (FDs) are the widely used shape descriptors. But FDs can only be used to objects with single boundary, and it is inapplicable to objects with several components. In this paper, a region-based method, which is called Polar Vector Fourier Descriptors (PVFDs), is developed to extract invariant features. Firstly, the Cartesian coordinate system is converted into polar coordinate system...
This article describes the detection of the characters of the license plate through of computer vision techniques: such as cascade of classifiers based in sobel algorithm, analysis of peaks and valleys, and support vector machines; the search for the region of the plate begins by detecting vehicles, then character segmentation and concludes with the recognition of these. The system was tested in different...
Text recognition in video/natural scene images has gained significant attention in the field of image processing in many computer vision applications, which is much more challenging than recognition in plain background images. In this paper, we aim to restore complete character contours in video/scene images from gray values, in contrast to the conventional techniques that consider edge images/binary...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.