ZÍDEK KAREL, KOUBEK TOMÁŠ, PROCHÁZKA DAVID, VYTEČKA MARCEL. 2015. Assistance System for Traffi c Signs Inventory. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 63(6): 2197-2204. We can see arising trend in the automotive industry in last years-autonomous cars that are driven just by on-board computers. The traffi c signs tracking system must deal with real conditions with data that are frequently obtained in poor light conditions, fog, heavy rain or are otherwise disturbed. Completely same problem is solved by mapping companies that are producing geospatial data for diff erent information systems, navigations, etc. They are frequently using cars equipped with a wide range of measuring instruments including panoramic cameras. These measurements are frequently done during early morning hours when the traffi c conditions are acceptable. However, in this time, the sun position is usually not optimal for the photography. Most of the traffi c signs and other street objects are heavily underexposed. Hence, it is diffi cult to fi nd an automatic approach that can identify them reliably. In this article, we focus on methods designed to deal with the described conditions. An overview of the state-of-the-art methods is outlined. Further, where it is possible, we outline an implementation of the described methods using well-known Open Computer Vision library. Finally, emphasis is placed on the methods that can deal with low light conditions, fog or other situations that complicate the detection process.
This article is focused on the design and implementation of the complex solution of the remote control of the industrial manipulator Katana 6M180. The main aim is to increase utilization of the machine and its monitoring, whereas the safety standards won’t be affected. Both parts of the design, the hardware as well as the software one, are discussed in this article. The hardware part consists of the protective cage, controllable lighting, power circuits, electronics, server, several cameras used for image processing of the working space and one IP camera used for monitoring. The software tools represent second main part of the described solution of the remote control. This software part of the solution consists of the main control software running on the server, the reservation system and third party software that solves connections between clients and the server. Special attention is paid to the implementation of safety elements, in order to increase the robustness of the whole system. The description of one resolved task that used the designed remote control system, is listed in the conclusion as a proof of concept. The task is focused on determining parameters of the objects in the working space of the manipulator.
We can see arising trend in the automotive industry in last years -autonomous cars that are driven just by on-board computers. The traffi c signs tracking system must deal with real conditions with data that are frequently obtained in poor light conditions, fog, heavy rain or are otherwise disturbed. Completely same problem is solved by mapping companies that are producing geospatial data for diff erent information systems, navigations, etc. They are frequently using cars equipped with a wide range of measuring instruments including panoramic cameras. These measurements are frequently done during early morning hours when the traffi c conditions are acceptable. However, in this time, the sun position is usually not optimal for the photography. Most of the traffi c signs and other street objects are heavily underexposed. Hence, it is diffi cult to fi nd an automatic approach that can identify them reliably. In this article, we focus on methods designed to deal with the described conditions. An overview of the state-of-the-art methods is outlined. Further, where it is possible, we outline an implementation of the described methods using well-known Open Computer Vision library. Finally, emphasis is placed on the methods that can deal with low light conditions, fog or other situations that complicate the detection process.
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