Andrea Teschioni

A new approach to vector median filtering based on space filling curves

The availability of a wide set of multidimensional information sources in different application fields (e.g., color cameras, multispectral remote sensing imagery devices, etc.) is the basis for the interest of image processing research on extensions of scalar nonlinear filtering approaches to multidimensional data filtering. A new approach to multidimensional median filtering is presented. The method is structured into two steps. Absolute sorting of the vectorial space based on Peano space filling curves is proposed as a preliminary step in order to map vectorial data onto an appropriate one-dimensional (1-D) space. Then, a scalar median filtering operation is applied. The main advantage of the proposed approach is the computational efficiency of the absolute sorting step, which makes the method globally faster than existing median filtering techniques. This is particularly important when dealing with a large amount of data (e.g., image sequences). Presented results also show that the filtering performances of the proposed approach are comparable with those of vector median filters presented in the literature.

ROC curves for performance evaluation of video sequences processing systems for surveillance applications

Performance evaluation of image processing intermediate results in video based surveillance systems is extremely important due to the variety of approaches to this task. An approach based on the use of receiver operating characteristics (ROC) curves in order to evaluate the performance of a vision complex system for surveillance purposes is presented. The ROC curves have already been used in other research fields such as in the comparison of edge detection algorithms or in the evaluation of artificial neural networks: in this case they are used in order to compare different parameters selections within a system for the localization of moving objects. The presented results show the possibility of using ROC curves as a means for evaluation and comparison of video based surveillance systems.

Performance Evaluation Strategies of an Image Processing System for Surveillance Applications

The research in the field of Advanced Video-based Surveillance (AVS) Systems is significantly increased in the last few years, mainly thanks to the greater opportunities offered by the tremendous rate of innovation in computer and communication technologies.

Non-Gaussian characterization of DS/CDMA noise in few-user systems with complex signature sequences

An higher order statistics (HOS) based analysis of the non-Gaussian characteristics of the DS/CDMA global noise and a non-Gaussian evaluation of the expected BER, in few-user systems with complex signature sequences, are performed. Different error-rate performances provided by binary Gold and four-phase even-odd equivalent-Gold (EOE-Gold) spreading sequences are also considered.

The PASSWORDS Project [intelligent video image analysis system]

The objective of the PASSWORDS Project is to design and develop a prototype of an intelligent video image analysis system for video surveillance and security applications, based on concrete needs expressed by potential users. The goal of the system developed within PASSWORDS is to detect certain dangerous situations in some scenes (e.g. vandalism in a metro station), providing for example a remote operator with an alarm signal. This paper illustrates the different steps which compose the PASSWORDS system, focusing the attention on the image processing module.

A Long Term Change Detection Method for Surveillance Applications

A Long Term Change Detection (CD) Method is presented by definition of a probabilistic model and the integration of two different informative sources. The model is described from a theoretical point of view and its real implementation by means of a bank of shift registers is presented. The algorithm is part of a surveillance system for unattended railway stations: results on a real image sequence confirm its validity.

Software Design and Simulation of a DS/CDMA Multimedia Transmission System for Remote Video—Surveillance Applications

The most recent developments in the research concerning the Video—Surveillance reveal an increasing interest related to the systems operating in remote modality. The applications of such systems generally concern the video—surveillance of unattended environments. A local elaboration system acquires images by video sensors, it processes the images and it sends the elaborated information to a remote control centre. A secure and noise—robust transmission link for the critical information is required. In this work, an innovative software design technique of a DS/CDMA multimedia transmission system is presented, together with the visual results related to the multimedia transmission simulation.

A new distance measure for vectorial rank-order filters based on space filling curves

A non-linear digital filter is presented in this paper: this filter aims at extending the concept of scalar rank-ordering in the case of multichannel images. The filter is based on two steps: (1) a transformation from a p-dimensional steps to a one-dimensional space by means of a space filling curve; (2) a scalar median filtering step. Results which demonstrate the advantages and the good restoration computational performances of the filter are shown.

A Markovian approach to color image restoration based on space filling curves

A method for color image restoration based on the concept of Markov random fields and space-filling curves is presented. This work is a vectorial extension of a scalar deterministic solution for Markov random fields (MRFs). The proposed method represents an efficient alternative to the use of the vectorial deterministic solution for MRFs. The application of the space filling curve transformation allows one to apply the MRF algorithm to a scalar image with N/sup 3/ grey levels (typically N=256). The scalar MRF approach is based on expressing the energy function by means of the Euclidean norm in the vectorial space. This approach implies a high computational load. The new method involves a computational load lower than the vectorial case because the energy function is presented in the scalar space obtained after space filling curve based transformation.

A Quantitative Methodology for Parameters Setting in 3D People Localization System for Surveillance Applications

In this paper a methodology for the evaluation of the parameters set characterising an image processing system for surveillance applications is presented.