Abstract

Forensic document verification presents a different and interesting set of challenges as opposed to traditional writer identification and verification tasks using natural handwriting. The handwritten data presented to a forensic examiner is often deliberately altered, in addition to being limited in quantity. Specifically, the alterations can be either forged, where one imitates another person’s handwriting; or repudiated, where one deliberately distorts his handwriting in order to avoid identification. In this paper, we present a framework to detect repudiation in forensic documents, where we only have one pair of documents to arrive at a decision. The approach generates a statistically significant confidence score from matching two documents, which can be used to screen the documents that are passed on to an expert examiner. The approach can be extended for detection of forgeries as well.

Abstract

Accurate registration of images is essential for many computer vision algorithms for medical image analysis, super-resolution, and image mosaicing. Performance of traditional correspondence-based approaches is restricted by the reliability of the feature detector. Popular frequency domain approaches use the magnitude of global frequencies for registration, and are limited in the class of transformations that can be estimated. We propose the use of local phase information for accurate image registration as it is robust to noise and illumination conditions and the estimates are obtained at sub-pixel accuracy without any correspondence computation. We form an overdetermined system of equations from the phase differences to estimate the parameters of image registration. We demonstrate the effectiveness of the approach for affine transformation under Gaussian white noise and varying illumination conditions.

Abstract

One of the prime challenges in designing a classifier for large-class problems such as Indian language OCRs is the presence of a large similar looking character set. The nature of the character set introduces problems with accuracy and efficiency of the classifier. Hierarchical classifiers such as Binary Hierarchical Decision Trees (BHDTs) using SVMs as component classifiers have been effectively used to tackle such large-class classification problems. The accuracy and efficiency of a BHDT classifier will depend on: i) the accuracy of the component classifiers, ii) the separability of the clusters at each node in a hierarchical classifier, and iii) the balance of the BHDT. We propose methods to tackle each of the above problems in the case of binary character images. We present a new distance measure, which is intuitively suitable when Support Vector Machines are used as component classifiers. We also propose a novel method for balancing the BHDT to improve its efficiency, while maintaining the accuracy. Finally we propose a method to generate overlapping partitions to improve the accuracy of BHDTs. Comparison of the method with other forms of classifier combination techniques such as 1vs1, 1vsRest and Decision Directed Acyclic Graphs shows that the proposed approach is highly efficient, while being comparable with the more expensive techniques in terms of accuracy. The experiments are focused on the problem of Indian language OCR, while the framework is usable for other problems as well

Abstract

A document image is composed of a variety of physical entities or regions such as text blocks, lines, words, figures, tables, and background. We could also assign functional or logical labels such as sentences, titles, captions, author names, and addresses to some of these regions. The process of document structure and layout analysis tries to decompose a given document image into its component regions and understand their functional roles and relationships. The processing is carried out in multiple steps, such as preprocessing, page decomposition, structure understanding, etc. We will look into each of these steps in detail in the following sections. Document images are often generated from ph

Abstract

This paper describes the procedure of vulnerability assessment of structures for site specific peak ground acceleration. The objective of this paper is to define the building classification and development of damage probability matrix which represent the vulnerability of structure. The organization of this paper is as follows. First, the types of the structures are reviewed and a classification of structure based on the available data with Vulnerability Atlas of India is done. Second, the description of methodologies developed under various organizations is studied, adopted and summarized. Third, the theoretical methodology of the vulnerability analysis using fragility curve parameters given by HAZUS and capacity curve generated using SAP2000 for typical structure are presented and performance of structure is calculated by using capacity spectrum method.

Abstract

Earthquake Problems are not new to the country. We have witnessed several moderate earthquakes in the last two decades causing innumerable property loss and life loss. In order to minimize the loasses. We need to raise the awareness about earthquake resistant design of structures. This can be achieved by spreading the information on hazard vulnerability and risk to concerend people.

Abstract

This paper describes the procedure of vulnerability assessment for building structures in AP India. The objective of this paper is to define the building classification and development of damage probability matrix using fragility curve parameters of the building structures in Andhra Pradesh by using the avaiable information in Vulnerability Atlas of India developed by Building Materials and Technology promotion council Govt. of India (BMTPC).

Abstract

Urbanization is rapidly increasing all over the world. Past two decades in India many cities have attracted large population. Reasons being the belief of better education health care job/business prospects etc. For meeting the demands of population density many high-rise structures and large public gathering places are emerging in cities. Places where few thousands of people can meet are quite common in major cities. It is due to this reason evacuation at the public gathering places has gained a lot of importance

Abstract

This paper considers the problem of unicasting in wireless ad hoc networks. Unicasting is the problem of finding a route between a source and a destination and forwarding the message from the source to the destination. In theory, models that have been used oversimplify the problem of route discovery in ad hoc networks. The achievement of this paper is threefold. First we use a more general model in which nodes can have different transmission and interference ranges and we present a new routing algorithm for wireless ad hoc networks that has several nice features. We then combine our algorithm with that of known greedy algorithms to arrive at an average case efficient routing algorithm in the situation that GPS information is available. Finally we show how to schedule unicast traffic between a set of source-destination pairs by providing a proper vertex coloring of the nodes in the wireless ad hoc network. Our coloring algorithm achieves a O(Δ)–coloring that is locally distinct within the 2-hop neighborhood of any node.

Abstract

Shortest path computation has always been a subject of study and research in the history of computer science. In this paper we introduce and initiate the study of the problem of finding the shortest path in a privacy preserving manner, in presence of single convex polygonal obstacle. We also propose an efficient, elegant and simple solution for the problem.