Browsing by Subject "kamera"

Nowadays there is a lot of discussion about climate change and climate change affects everyone. In agriculture when studying the carbon cycle, it is essential to know and understand what is happening underground. Organic carbon bound to the soil is about 1500 Gt when measured from a depth of 1 m. According to the datasets in topsoil, at a depth of 0–30 cm, the amount of organic carbon is about 50 % of the total amount of organic carbon. For surface and subsoil examination the minirhizotron system provides an inexpensive and simple way to examine the roots of plants without destroying the plants examined. The objective of this study is to build and test a minirhizotron camera and scanner as well as to become familiar with image processing and its automation. The construction of the camera was started from an old minirhizotron camera which could be used as parts for a new one. The parts which could not be used from the old camera were designed with 3D modeling software and manufactured with 3D printer. For image acquisition an electronic microscope was bought. For the scanner system a normal USB powered flatbed scanner was purchased and a protective case was built for it. Imaging with a minirhizotron camera transparent tubes must be installed to the ground and they are usually installed vertically, horizontally, or at an angle of 30 ° to 45 °. The way that a scanner is installed is usually determined by what the purpose of the imaging is. The obtained image material showed that the self-built minirhizotron system is a suitable tool for root research and its relatively inexpensive price allows a wide distribution of the system, even among ordinary farmers. A prerequisite for the success of the images is close contact between the ground and the tubes or scanner. It allows the images to be accurately thresholded and gives reliable results when analyzing the images. Highlighting the roots by hand is very time consuming which is the reason that development of automatic analyzing is needed. Successful thresholding is also a prerequisite for the automation and it should be noted in the future. Viability of machine vision and machine learning in root studies should be studied.

The study examines various uses of computer technology in acquisition of information for visually impaired people. For this study 29 visually impaired persons took part in a survey about their experiences concerning acquisition of infomation and use of computers, especially with a screen magnification program, a speech synthesizer and a braille display. According to the responses, the evolution of computer technology offers an important possibility for visually impaired people to cope with everyday activities and interacting with the environment. Nevertheless, the functionality of assistive technology needs further development to become more usable and versatile. Since the challenges of independent observation of environment were emphasized in the survey, the study led into developing a portable text vision system called Tekstinäkö. Contrary to typical stand-alone applications, Tekstinäkö system was constructed by combining devices and programs that are readily available on consumer market. As the system operates, pictures are taken by a digital camera and instantly transmitted to a text recognition program in a laptop computer that talks out loud the text using a speech synthesizer. Visually impaired test users described that even unsure interpretations of the texts in the environment given by Tekstinäkö system are at least a welcome addition to complete perception of the environment. It became clear that even with a modest development work it is possible to bring new, useful and valuable methods to everyday life of disabled people. Unconventional production process of the system appeared to be efficient as well. Achieved results and the proposed working model offer one suggestion for giving enough attention to easily overlooked needs of the people with special abilities. ACM Computing Classification System (1998): K.4.2 Social Issues: Assistive technologies for persons with disabilities I.4.9 Image processing and computer vision: Applications