Tomislav Keser

Failure detection and isolation in ceramic tile edges based on contour descriptor analysis

Todays industry is based on the principle of automatics. In order to increase production quality and improve production yield that reduces production costs, there is tendency to automate every phase in the production line and if possible to replace the human resource entirely. Ceramic tile industry is not an exception. In the ceramic tile production line almost every phase is more or less automated. The only part which is least automated is visual inspection and classification of a ceramic tile. In this paper we present a method for visual inspection of ceramic tile edges, their failure detection and isolation using a machine vision system. For edges inspection, detection and failure isolation we use a method based on contour tracing and description of tile edges. The method developed generates a contour reference descriptor based on directional contour tracing, determines tile orientation for referenced preprocessing and localizes and isolates the failure. The method is tested and results are given for several types and sizes of ceramic tiles.

A Simple and Efficient Method for Ceramic Tile Surface Defects Detection

In this paper is developed and presented method for failure detection in ceramic tile production using computer visual diagnostic. This method is focused on detecting of failures on ceramic tile surface in manner of highly contrasted dot shaped formation incorporated into ceramic tile surface which are result of failures in production chain. The ceramic tile quality grade is directly influenced by amount and type of failures on its surface and with presented method in this paper we try to contribute to automating of final stages in ceramic tile producing chain. This presented and developed method is optimized for fast execution and for efficient detection of mentioned failures without need for reference tile comparison system.

Distributed intelligent control of car lighting system with fault detection

The developed system for distributed intelligent control of automotive lighting system is presented in this paper. Control system is based on distributed microcontroller system and its control algorithms. A technique for intelligent light intensity control based on pulse width modulation is presented and comparison with traffic safety law regulations is given. A subsystem for failure detection and adaptation in case of failure appearances caused by hardware or communication malfunction of vehicle lighting system is built into control system. For analog signal measuring purposes are presented and applied techniques for signal filtering by using fast convolution based methods.

Traffic Sign Shape Detection and Classification based on the Segment Surface Occupancy Analysis and Correlation Comparisons

This article addresses the issue of traffic sign recognition. It contributes to a growing body of research done by the automotive industry due to a necessity for ensuring better safety on the roads. This paper presents a novel method for traffic signs recognition. The implementation of the whole process of traffic sign recognition has a step-wise nature but the novelty is introduced into the traffic sign shape detection stage. The method is based on a new approach for traffic sign shape recognition based on the image content occupancy analysis. Further, the traffic sign content classification is based on a simplistic relational correlation analysis. The tests were performed on image data comprising various roads and lighting conditions. The test includes different sizes of templates used in the correlation comparison method. The results are presented in a manner of successfulness of the correct recognition.

Wearing characteristics assessment of pervious concrete pavements

Seven different concrete mixtures were prepared to estimate the possibility of using pervious concrete for light traffic urban areas. The total porosity, density, compressive strength, flexural strength, abrasion resistance, and traffic noise absorption capacity were tested for all the concrete specimens. The first mixtures corresponded to a standard dense concrete mixture (M1), while the other mixtures were pervious concrete mixtures involving two different types of aggregates (dolomite and steel slag) and different proportions of aggregate fractions. The total porosity, density, compressive strength, flexural strength, abrasion resistance, and traffic noise absorption capacity were tested in the case of all concrete specimens. The total porosity increased, whereas the compressive and flexural strength decreased simultaneously with an increase in the share of coarse aggregate fractions. The abrasion resistance and acoustic characteristics improved if only a fraction of the aggregate was used in pervious concrete preparation.

Infrared thermography as control of handheld IPL device for home-use

ABSTRACT Infrared thermography as contactless method for determining the temperature distribution on the surface is used for analyzing the impact of intense pulsed light hair removal device (IPL) on the skin. Depth of light penetration depending of wavelength is described as well as absorption curves and IPL impulse shapes. Energy balance and IPL impulse influence on the skin is analyzed. Melanin temperature rise by different fluence operation and temperature distribution in the modeled hair is used in order to determine overall skin temperature rise. Estimated energy balance provided by mathematical model has been confirmed with experimental results. Performed measurements, beside determination of the right emissivity, required the identification of most significant parameter in the process which proved to be the skin reference temperature and real temperature rise. Practical IPL application with detailed body temperature analysis is comprehensively described and thermal imaging interpretation problem and determination of the temperature rise is observed.

Traffic signs shape recognition based on contour descriptor analysis

Methods for automated traffic sign detection and recognition represents one of many structural pillars and basic building blocks in autonomous and self-aware transportation systems. Computationally efficient and recognition successful methods have great importance in accomplishments of such tasks. This paper presents a novel technique for traffic signs shape recognition that is based on analysis of the signs shape contour descriptors. The primary task of the presented method is proper recognition and classification of signs by their shapes into three basic categories; circle, triangle and square/rectangle one. The method utilizes a shape contour description in the manner of absolute angular tracing characteristics of a sign shape. Contour descriptors of different sign shapes in various imaging condition are analyzed, results are shown and evaluated. The presented method successfully distinct traffic signs by their shapes and proves the method usability.