Abstract

In this paper we describe a prototype system that recognizes text in images, captured by camera phones and provide access to the content in a different language. Two Indian languages – Hindi and Tamil are used to demonstrate such a system. The prototype system is built using off-the-shelf components, and in house developed algorithms. The acquired image is first transferred to a server, which corrects the perspective distortions, detects recognizes and then translates the text (word). This translated text is sent back to the camera-phone in a suitable form. We have also described here, the Hindi and Tamil OCRs which we use for the character recognition. We also propose methods to make the recognizer efficient in storage and computation. The translated text, along with any additional information, is transmitted back to the user.

Abstract

A discriminant-based framework for automatic recognition of online handwriting data is presented in this paper. We identify the substrokes that are more useful in discriminating between two online strokes. A similarity/dissimilarity score is computed based on the discriminatory potential of various parts of the stroke for the classification task. The discriminatory potential is then converted to the relative importance of the substroke. Experimental verification on online data such as numerals, characters supports our claims. We achieve an average reduction of
 in the classification error rate on many test sets of similar character pair

Abstract

In Africa, there are a number of languages with their own indigenous scripts. This paper presents an OCR for Amharic scripts. Amharic is the official and working language of Ethiopia. This is possibly the first attempt towards the development of an OCR system for Amharic. Research in the recognition of Amharic script faces major challenges due to (i) the use of more than 300 characters in writing and (ii) existence of a large set of visually similar characters. In this paper, we propose a two-stage feature extraction scheme using PCA and LDA, followed by a decision DAG classifier with SVMs as the nodes. Recognition results are presented to demonstrate the performance on the various printing variations (fonts, styles and sizes) and real-life degraded documents such as books, magazines and newspapers.

Abstract

In this paper we describe a spectrum of algorithm for rectification of document images of camera based analysis and recognition. Clues like document boundaries page ,page layout information, organisation of text and graphics, components, apriori knowledge of script or selected symbols etc. are effectively used for removal of perspective effect and comforting the frontal view needed for a typical document image analysis algorithm. Appropriate results from projective geometry for planar surfaces are exploited in these situations.

Abstract

In this paper we propose a novel technique for robust visual servoing in presence of a large proportion of outliers in image measurements. The method employs robust statistical techniques and novel view prediction for improving the performance. We identify a set of points from initial and reference images and compute the essential matrix relating them. The selected points are predicted from the initial and reference images to the current frame using essential matrices. A function of the difference between the observed and predicted image point measurements is used to identify outliers. This technique is validated with many experiments and compared with other robust methods in a simulation framework.

Abstract

Many of the human activities such as Jumping, Squatting have a correlated spatiotemporal structure. They are composed of homogeneous units. These units, which we refer to as actions, are often common to more than one activity. Therefore, it is essential to have a representation which can capture these activities effectively. To develop this, we model the frames of activities as a mixture model of actions and employ a probabilistic approach to learn their low-dimensional representation. We present recognition results on seven activities performed by various individuals. The results demonstrate the versatility and the ability of the model to capture the ensemble of human activities.

Abstract

Digital Libraries have received wide attention in the recent years allowing access to digital information from anywhere across the world. They have become widely accepted and even preferred information sources in areas of education, science and others. When the full potential of digital libraries is realized, any citizen will for the first time be able to access all human knowledge immediately from any location. For a successful and useful Digital Library, the assurance of quality of the product from digitization process is quite essential. In this paper we discuss the major quality concerns of data from the digitization process, and how we assure for better quality before they are web enabled for the end-user to use. Also we discuss a Quality Management Framework that we applied for the improvement of both the Quality of the digital output and the efficiency of the processes.

Abstract

Computing the transformation between two views of a planar scene is an important step in many computer vision applications. Spatial approaches to solve this problem need corresponding sets of primitives – points, lines, conics, etc. Identification of corresponding primitives in two images is non-trivial, limiting the applicability of such approaches. In this paper, we present a novel Fourier domain based approach that makes use of image intensities for computing the image-to-image transformation. Our approach transforms the images to the Fourier domain and then represents them in a coordinate system in which the affine transformation is reduced to an anisotropic scaling. The anisotropic scale factors can be computed using cross correlation methods, and working backwards from this, we compute the entire transformation. It does not require any correspondences thereby making it practically very useful. Applications to registration and recognition are discussed.

Abstract

Recognition of discrete planar contours under similarity transformations has received a lot of attention but little work has been reported on recognizing them under more general transformations. Planar object boundaries undergo projective or affine transformations across multiple views. We present two methods to recognize discrete curves in this paper. The first method computes a piecewise parametric approximation of the discrete curve that is projectively invariant. A polygon approximation scheme and a piecewise conic approximation scheme are presented here. The second method computes an invariant sequence directly from the sequence of discrete points on the curve in a Fourier transform space. The sequence is shown to be identical up to a scale factor in all affine related views of the curve. We present the theory and demonstrate its applications to several problems including numeral recognition, aircraft recognition, and homography computation. q 2004 Elsevier B.V. All rights reserved

Abstract

This paper presents several results on images of various configurations of conics. We extract information about the plane from single and multiple views of known and unknown conics, based on planar homography and conic correspondences. We show that a single conic section cannot provide sufficient information. Metric rectification of the plane can be performed from a single view if two conics can be identified to be images of circles without knowing their centers or radii. The homography between two views of a planar scene can be computed if two arbitrary conics are identified in them without knowing anything specific about them. The scene can be reconstructed from a single view if images of a pair of circles can be identified in two planes. Our results are simpler and require less information from the images than previously known results. The results presented here involve univariate polynomial equations of degree 4 or 8 and always have solutions. Applications to metric rectification, homography calculation, 3D reconstruction, and projective OCR are presented to demonstrate the usefulness of our scheme