Abstract

This paper presents the detailed seismic hazard assessment of the peninsular India (lat. 8°-28°N and long. 67.5°-90°E) which is considered to be seismically most stable landmasses of the Indian plate. Past seismic history in this region (Koyna, 10 December 1967; Bhadrachalam, 13 April 1969; Broach, 23 March 1970; Hyderabad, 30 June 1983; Latur, 30 September 1993; Jabalpur, 22 May 1997; Bhuj, 26 January 2001 etc) clearly shows that the seismicity of the area is varying. There were more than five damaging earthquakes with magnitudes greater than Mw 6.0 have occurred in this region, stressing the importance of detailed seismic hazard assessment for the region. For India, Bhatia et al. (1999) published a probabilistic seismic hazard map based on several well identified and prominent source zones in the country. An attempt has been made in this paper to study the present seismic status of this region incorporating the seismicity, tectonic and geological characteristics and using the collected earthquake data Peak Ground Acceleration was estimated using the attenuation relation developed by Iyengar and Raghukanth (2004). Estimated PGA values were used to compute the deviation with respect to assigned PGA values for various regions provided in Indian Standard code IS 1893:2002. The results show that, the estimated PGA in many areas of the Peninsular India is more than the specified value in the current seismic macrozonation map of the country. This provides an important basis for attempting the detailed microzonation of an area within the Penisular India.

Abstract

Indian Subcontinent is one of the seismically active regions of the world. The seismicity of India can be divided into 4 groups: Himalayan Region, Indo-Gangetic Plain, Kutch-Kathiawar Region and the Peninsular India (Ref EU Report 2003). Himalayas are one of the rare sites of continent to continent collision and also tectonically very active belt. The high seismicity of the region can be observed from the past events occurred in the region as shown in Figure.1. Depending on the past earthquakes, Bureau of Indian Standards has prepared the Seismic Zonation map of India (IS-1893-2002), which divides the country into 4 different zones. As per the zonation map 57% land of the country falls under high seismic zone. These maps do not consider the frequency of occurrence of earthquakes; hence they do not divide the country into regions of equal hazard and risk. For cultural heritage and other important structures, these maps act only as a guideline for the expected intensities. For those structures, site specific seismic hazard maps have to be generated specially for use. Rigorous quantifications of seismic hazard in detail for the Delhi region have not been carried out so far. Chouhan (Proc.INSA) estimated the focal depth of earthquake around Delhi to be about 8 km. His frequency-magnitude analyses lead to the conclusion that the maximum size of an earthquake that may occur in this region would be 7.6. The work of Srivastav and Roy (1982) indicates that in a period of 50 years a magnitude 6 earthquakes are almost certain and that there is 80% probability of a 7 magnitude event visiting the region. Khattri (1992) has carried out an exercise estimating the seismic hazard for the northern region of the country. According to this study in a fifty year window of 1983 - 2033, the peak ground accelerations around Delhi would be 0.2 g with 10% probability of exceedence. Delhi and its environs have not yet experienced this level of ground vibration in the above time period. Even if these estimates need further refinement they indicate the nature of events expected for Delhi city (Iyengar, 2000). Keeping in view all these studies, the effect of any future earthquake in Delhi region is studied in this paper.

Abstract

This paper presents the detailed seismic hazard assessment of the peninsular India (lat. 8°-28°N and long. 67.5°-90°E) which is considered to be seismically most stable landmasses of the Indian plate. Past seismic history in this region (Koyna, 10 December 1967; Bhadrachalam, 13 April 1969; Broach, 23 March 1970; Hyderabad, 30 June 1983; Latur, 30 September 1993; Jabalpur, 22 May 1997; Bhuj, 26 January 2001 etc) clearly shows that the seismicity of the area is varying. There were more than five damaging earthquakes with magnitudes greater than Mw 6.0 have occurred in this region, stressing the importance of detailed seismic hazard assessment for the region. For India, Bhatia et al. (1999) published a probabilistic seismic hazard map based on several well identified and prominent source zones in the country. An attempt has been made in this paper to study the present seismic status of this region incorporating the seismicity, tectonic and geological characteristics and using the collected earthquake data Peak Ground Acceleration was estimated using the attenuation relation developed by Iyengar and Raghukanth (2004). Estimated PGA values were used to compute the deviation with respect to assigned PGA values for various regions provided in Indian Standard code IS 1893:2002. The results show that, the estimated PGA in many areas of the Peninsular India is more than the specified value in the current seismic macrozonation map of the country. This provides an important basis for attempting the detailed microzonation of an area within the Penisular India

Abstract

In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserves the local similarity structure. A method to find the approximate nearest neighbor of a query is proposed, that drastically reduces the total number of explicit distance measures that need to be computed. The representation overcomes the restrictive assumptions in traditional manifold mappings, while enabling fast nearest neighbor’s search. Experimental results on the Unipen and CASIA Iris datasets clearly demonstrates the advantages of the approach and improvements over state of the art algorithms. The algorithm can work in batch mode as well as in sequential mode and is highly scalable.

Abstract

A palmprint based authentication system that can work with a multipurpose camera in uncontrolled circumstances, such as those mounted on a laptop, mobile device or those for surveillance, can dramatically increase the applicability of such a system. However, the performance of existing techniques for palmprint authentication fall considerably, when the camera is not aligned with the surface of the palm. The problems arise primarily due to variations in appearance introduced due to varying pose, but is compounded by specularity of the kin and blur due to motion and focus. In this paper, we propose a method to deal with variations in pose in unconstrained palmprint imaging. The method can robustly estimate and correct variations in pose, and compute a similarity measure between the corrected test image and a reference image. Experimental results on a set of 100 user’s palms captured at varying poses show a reduction in Equal Error Eate from 22.4% to 8.7%.

Abstract

Biometric authentication over public networks leads to a variety of privacy issues that needs to be addressed before it can become popular. The primary concerns are that the biometrics might reveal more information than the identity itself, as well as provide the ability to track users over an extended period of time. In this paper, we propose an authentication protocol that alleviates these concerns. The protocol takes care of user privacy, template protection and trust issues in biometric authentication systems. The protocol uses asymmetric encryption, and captures the advantages of biometric authentication. The protocol provides non-repudiable identity verification, while not revealing any additional information about the user to the server or vice versa. We show that the protocol is secure under various attacks. Experimental results indicate that the overall method is efficient to be used in practical scenarios.

Abstract

We propose an approach to restore severely degraded document images using a probabilistic context model. Unlike traditional approaches that use previously learned prior models to restore an image, we are able to learn the text model from the degraded document itself, making the approach independent of script, font, style, etc. We model the contextual relationship using an MRF. The ability to work with larger patch sizes allows us to deal with severe degradations including cuts, blobs, merges and vandalized documents. Our approach can also integrate document restoration and super-resolution into a single framework, thus directly generating high quality images from degraded documents. Experimental results show significant improvement in image quality on document images collected from various sources including magazines and books, and comprehensively demonstrate the robustness and adaptability of the approach. It works well with document collections such as books, even with severe degradations, and hence is ideally suited for repositories such as digital libraries

Abstract

Search and retrieval is gaining importance in the ink domain due to the increase in the availability of online handwritten data. However, the problem is challenging due to variations in handwriting between various writers, digitizers and writing conditions. In this paper, we propose a retrieval mechanism for online handwriting, which can handle different writing styles, specifically for Indian languages. The proposed approach provides a keyboard-based search interface that enables to search handwritten data from any platform, in addition to pen-based and example-based queries. One of the major advantages of this framework is that information retrieval techniques such as ranking relevance, detecting stopwords and controlling word forms are extended to work with search and retrieval in the ink domain. The framework also allows cross-lingual document retrieval across Indian languages

Abstract

Writer independent handwriting recognition systems are limited in their accuracy, primarily due the large variations in writing styles of most characters. Samples from a single character class can be thought of as emanating from multiple sources, corresponding to each writing style. This also makes the inter-class boundaries, complex and disconnected in the feature space. Multiple kernel methods have emerged as a potential framework to model such decision boundaries effectively, which can be coupled with maximal margin learning algorithms. We show that formulating the problem in the above framework improves the recognition accuracy. We also propose a mechanism to adapt the resulting classifier by modifying the weights of the support vectors as well as that of the individual kernels. Experimental results are presented on a data set of 16,000 alphabets collected from 470 writers using a digitizing tablet

Abstract

Widespread use of surveillance cameras in offices and other business establishments, pose a significant threat to the privacy of the employees and visitors. The challenge of introducing privacy and security in such a practical surveillance system has been stifled by the enormous computational and communication overhead required by the solutions. In this paper, we propose an efficient framework to carry out privacy preserving surveillance. We split each frame into a set of random images. Each image by itself does not convey any meaningful information about the original frame, while collectively, they retain all the information. Our solution is derived from a secret sharing scheme based on the Chinese Remainder Theorem, suitably adapted to image data. Our method enables distributed secure processing and storage, while retaining the ability to reconstruct the original data in case of a legal requirement. The system installed in an office like environment can effectively detect and track people, or solve similar surveillance tasks. Our proposed paradigm is highly efficient compared to Secure Multiparty Computation, making privacy preserving surveillance, practical.