Andrea Guerriero

Selection of reference signatures for automatic signature verification

This paper presents an effective procedure to select the reference specimens for a signature verification system. Specifically, from the analysis of local stability in handwritten signatures, a suitable measure is proposed to determine the capability of different sets of signatures in supporting effective verification. The measure uses a correlation-based criterium which detects and recovers non-linear time distortions in different specimens. In the experimental test, the selected set of signatures has been used for reference in a system for dynamic signature verification based on a multi-expert verification strategy. The experimental results points out the capability of the new technique in selecting effective reference signatures.

A Multi-expert System for Dynamic Signature Verification

This paper presents a multi-expert system for dynamic signature verification. The system combines three experts whose complementar behaviour is achieved by using both different features and verification strategies. The first expert uses shape-based features and performs signature verification by a wholistic analysis. The second and third expert uses speedbased features and performs signature verification by a regional analysis. Finally, the verification responses provided by the three experts are combined by majority voting.

An Evaluation of the Effectiveness of Image Features for Image Retrieval

Retrieval effectiveness in image databases depends significantly on the features and the distance model utilized to evaluate the similarity of the images. Features must be extracted from images and stored in the database. Since the features should be stored at the time of data entry, it is extremely important to determine which features ensure the best retrieval performances. In this paper a comparison of the most widespread automatic indexing techniques and their performances is presented. The image reference set, necessary for performance comparison, is obtained by including in the database frames extracted from video shots. Frames extracted from a shot are different but have the same semantic content. One of these frames is utilized as an example in a query; the indexing effectiveness is assessed from the frames retrieved. The most relevant features prove to be the angular spectrum, the Hough transform, and the color histogram, followed by local features such as local luminance pattern directionality.

A dynamic URL assignment method for parallel web crawler

A web crawler is a relatively simple automated program or script that methodically scans or “crawls” through Internet pages to retrieval information from data. Alternative names for a web crawler include web spider, web robot, bot, crawler, and automatic indexer. There are many different uses for a web crawler. Their primary purpose is to collect data so that when Internet surfers enter a search term on their site, they can quickly provide the surfer with relevant web sites. In this work we propose the model of a low cost web crawler for distributed environments based on an efficient URL assignment algorithm. The function of every module of the crawler is analyzed and main rules that crawlers must follow to maintain load balancing and robustness of system when they are searching on the web simultaneously, are discussed. The proposed a dynamic URL assignment method, based on grid computing technology and dynamic clustering, results efficient increasing web crawler performance.

A Comparative Evaluation of Retrieval Methods for Duplicate Search in Image Database

Abstract Visual database systems are continuously enriched by original and processed images derived from the original using editing techniques. This last type of image (called duplicate) represents a relevant quote of unnecessary stored images and, moreover a clear case of image similarity. In this paper a comparative evaluation between image retrieval methods in the specific case of duplicate search is proposed. All methods are based on low-level features extraction, such as colors, shape and patterns, and are suitable in automatic systems. The performance comparison is made in terms of effectiveness using a database of 6368 natural pictures and 12 test sets of 18 images each.

Image basic features indexing techniques for video skimming

In this paper a comparison of the most widespread automatic indexing techniques, suitable in skimmed video generation, and their performances is presented. To evaluate the performances, using the low-level frame features, the signatures are computed, the shots are identified using neural network clustering techniques, in each shot the mean distance between contiguous frames is computed and the shot is resampled according to a related distance value to produce a skimmed video sequence. The most relevant feature proves to be the angular spectrum. Using this feature the mean value of the skimming factor is 2.6 in the used test set.

Electronic document image resizing

Computer document treatment generally requires specific techniques to handle documents. Among the others one of great interest is resizing. The effect of resizing is more evident when thin lines are included in the document. In this case a high degradation and consequently great loss of information occurs. In this paper different reduction techniques, in terms of computational load and information loss referred to graphics and technical drawings, are compared. Experimental results, related to document treatments, are included in the paper. The results are obtained using a threshold technique optimized for line drawing reduction.

A Data Warehouse for earthquakes signal precursors analysis

Earthquake analysis and monitoring requires complex processing of raw data acquired from several kind of sensors or extracted from data repositories. Management and processing of huge amount of data produced by different sources, i.e. remote sensing and measurement stations of ground and atmospheric physical parameters, the complexity of the environmental models adopted to understand observed phenomena, the necessary distributed collaboration among scientists, results sharing and validation, require specific middleware and applications. A number of researches propose to transform acquired data into assessments of current ecosystem conditions and its evolution trends in time and space; many algorithms, protocols, and applications have been presented to collect, process and analyze ground precursors representing changes in the physical and chemical state of the Earth. These projects deal with data obtained i.e. from satellite, VLF signal and INGV database, integrated with meteorological data and stored in ad hoc repositories. No work deals with a general and flexible approach to integrate and manage different kind of data. In this paper we present a data warehouse to analyze earthquake signal precursors, whose goal is to fuse and exploit efficiently different kind of data and share/display the processing results. The proposed platform allows users/researches: to access data collected by different sources, to record data for future use, to normalize and visualize data for exploring and analyzing complex structure and relationships, and to process data using distributed computing resources and web applications. A case study related to data fusion of INGV data, magnetic field variations acquired by a network of VLF radio stations, MODIS data to evaluate modification in the ground temperature by satellite and geo-located sensor data of weather and climatic parameters is presented.

Java based architecture for grid applications

Environments that integrate network computer into global computing resources have been studied since the development of Internet. In order to provide a platform independent approach to high-performance network computing, several Java-based implementations have been developed. Java overcomes the issue of maintaining different binary codes, multiple execution environments, and complex architectures. It offers the basic infrastructure to integrate computers resources connected to Internet into a distributed computational resource and allows parallel applications execution on different O.S. environment. In this paper we discuss the design and implementation of a network computing prototype system based on Java technology. The proposed multi level architecture uses the Agent paradigm to manage resources and to develop a user friendly interface to share resources in the grid.

Resources and jobs fuzzy classification in a java based grid architecture

Grid computing allows integration of geographically distributed resources, belonging to different Organization, to obtain huge computational power and data management capability that usually cannot be owned by a single computational system. Utilization of this powerful technology is mainly conditioned by tricky management of different architectures and environments and by the difficulty to identify an efficient resources selection to map grid task into grid resources that dynamically vary their features. In this paper we discuss the design and implementation of a network computing prototype system based on Java technology. The proposed multi level architecture uses the Agent paradigm to manage different complex architectures and fuzzy similarity measures to find the appropriate resource that meets task needs.