With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-resea...With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-research progress on diagnosis of agricultural products, water diagnosis, weed identification,product quality testing and grading, agricultural picking and sorting and other as- pects, and finally put forward its existing problems and prospects for the future.展开更多
The correct use of information in science and technology is very important for its progress. Nowadays, the equipment used for the scientific and technological development provides results that are later interpreted by...The correct use of information in science and technology is very important for its progress. Nowadays, the equipment used for the scientific and technological development provides results that are later interpreted by the researchers, in most of the above mentioned equipment the results are images full of information which has to be analyzed. A powerful stage with multiple benefits in this field is the image pre-processing by means of intelligent systems, which are capable to do image analysis throwing very useful results that enhance the scientific and technological information. There are currently more than 500 functions in the computational vision specialized open source library OpenCV, which associated with the C＋＋ programming language. These functions are used for application development in many areas of computer vision such as products inspection, medical images, safety, user＇s interfaces, camera calibration, stereoscopic vision and robotics. In this development and research work, by using the available functions and modifying the exposed methods, we present a proposal for signal detection in images originated in the transmission electron microscope （known as diffraction patterns）, which are attached to the detailed analysis of crystalline structures used in the study of the materials science, the results show a profit of at least 18% in the detection of signs by means of the method proposed in this work.展开更多
文摘With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-research progress on diagnosis of agricultural products, water diagnosis, weed identification,product quality testing and grading, agricultural picking and sorting and other as- pects, and finally put forward its existing problems and prospects for the future.
文摘The correct use of information in science and technology is very important for its progress. Nowadays, the equipment used for the scientific and technological development provides results that are later interpreted by the researchers, in most of the above mentioned equipment the results are images full of information which has to be analyzed. A powerful stage with multiple benefits in this field is the image pre-processing by means of intelligent systems, which are capable to do image analysis throwing very useful results that enhance the scientific and technological information. There are currently more than 500 functions in the computational vision specialized open source library OpenCV, which associated with the C＋＋ programming language. These functions are used for application development in many areas of computer vision such as products inspection, medical images, safety, user＇s interfaces, camera calibration, stereoscopic vision and robotics. In this development and research work, by using the available functions and modifying the exposed methods, we present a proposal for signal detection in images originated in the transmission electron microscope （known as diffraction patterns）, which are attached to the detailed analysis of crystalline structures used in the study of the materials science, the results show a profit of at least 18% in the detection of signs by means of the method proposed in this work.
