This paper is about different techniques for intelligent processing of data obtained with water quality monitoring distributed systems. The techniques include a set of fuzzy neural networks (FuNNs) for modelling measuring channels and Kohonen Self Organizing Maps (K-SOMs) for information classification. Elements of FuNN and K-SOM optimization in terms of architecture and training are presented and briefly discussed.

In this paper we propose a criterion for uncertainty evaluation in a color quality control. In a joint project between two laboratories of the Faculty of Engineering in Florence we study a PC-CCD system, called Textile Color Match (TCM) for the digital acquisition of the colorimetric coordinates of a wool sample. One of the main result is the achievement of a threshold of tolerance for the reproduction of this colored sample.

This paper addresses the problem of recognition and identification of objects with an IR diode array, working on a reflection light scanner principle. Essentially two arrays comprising of 3 emitter-receiver pairs are mounted on two sides of the area of inspection, enabling the estimation of the size of the object in different dimensions and reducing the requirements with regard to the detection range. The sensors are driven successively in time, hence no signal overlapping and cross-talk occur. For the recognition, a neural network approach based on the Backpropagation algorithm has chosen. The array data are preprocessed via a Principal Components approach. As a result various objects can be recognised and classified easily and are well separable from other echoes. This work is preliminary for a practical system determining the number of people and identifying people getting into or out of a room and other applications supporting important home appliances like occupation-driven HVAC control or determining behaviour patterns.

A technique to automatically configure an environment map using image processing is proposed in this paper. An autonomous mobile robot, which we are developing travels in indoor environment while referring to the environment map. This technique does not need a great cost in a measurement and can support a change of more indoor environment. Taking the indoor environment by a moving CCD camera, a continuation image is acquired. For each frame image of the continuation image, optical-flow estimation is computed. Straight line elements are extracted from an individual frame image. The straight line elements are chased between frames using an optical-flow estimation. By repeating such an operation, correspondence of straight line elements between the initial frame and the last frame is decided. By applying 3-D stereography to these two frames, 3-D information of the indoor environment is detected. In this paper, several techniques and new technique of the optical-flow estimation are explained. By an experiment, the effectiveness of the new technique is shown.

Speckle-interferometry is a very interesting group of measurement methods based on coherent light dissipation properties. There are a lot of applications of this effect, but the most interesting one is shape-measurement. It is astonishing that a nearly random structure of speckle image can contain information about the contour of the object illuminated by coherent light. The method is well-known but it is not so popular because of great disadvantage: method needs very good stability of the measurement object and instrument. So this technique was applied only in laboratory for a long time.
In this article we want to present special algorithms and setups which permit applying speckle-interferometry out of the lab – in industrial conditions.