Method for Signals Detection in Single Crystal Diffraction Patterns through a Diffraction Pattern Indexing Software
Method for Signals Detection in Single Crystal Diffraction Patterns through a Diffraction Pattern Indexing Software作者机构：Division de Estudios de Posgrado-Departamento de Sistemas y Computacion Instituto Tecnologico de Chihuahua II Chihuahua 31130 Mexico Centro de Investigacion en Materiales Avanzados S.C. Laboratorio Nacional de Nanotecnologia Miguel de Cervantes No. 120 Chihuahua Chih. C.P. 311136 Mexico
出 版 物：《Journal of Mechanics Engineering and Automation》 (机械工程与自动化（英文版）)
年 卷 期：2015年第5卷第9期
页 面：525-532页
学科分类：07[理学] 08[工学] 080203[工学-机械设计及理论] 070104[理学-应用数学] 0802[工学-机械工程] 081101[工学-控制理论与控制工程] 0701[理学-数学] 0811[工学-控制科学与工程]
主 题：Diffraction pattern OpenCV detection image pre-processing.
摘 要：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.
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