Developing a Computer Vision System for Real-Time Color Measurement – A Case Study with Color Characterization of Roasted Rice

2021 ◽  
pp. 110821
Author(s):  
Chanh-Nghiem Nguyen ◽  
Van-Thoai Vo ◽  
Cong Ha Nguyen
2011 ◽  
Vol 76 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Peter Ahrendt ◽  
Torben Gregersen ◽  
Henrik Karstoft

Author(s):  
D. Y. Erokhin ◽  
A. B. Feldman ◽  
S. E. Korepanov

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.


2018 ◽  
Vol 27 (05) ◽  
pp. 1
Author(s):  
Saulo Martielo Mastelini ◽  
Matheus Gustavo Alves Sasso ◽  
Gabriel Fillipe Centini Campos ◽  
Marcio Schmiele ◽  
Maria Teresa Pedrosa Silva Clerici ◽  
...  

1991 ◽  
Author(s):  
Fang-Fang Yin ◽  
Maryellen L. Giger ◽  
Kunio Doi ◽  
Carl J. Vyborny ◽  
Robert A. Schmidt ◽  
...  

2020 ◽  
Vol 40 (1) ◽  
pp. 21
Author(s):  
Ferlando Jubelito Simanungkalit ◽  
Rosnawyta Simanjuntak

Color had a correlation with physical appearance, nutritional and chemical content as well as sensory properties which determine the quality of agricultural products and foods. Conventional color measurements were performed destructively using laboratory equipment. Therefore, color measurement methods of agricultural products were needed more quickly, accurately and non-destructively. This study aimed to develop a Computer Vision System (CVS) that can be used as a tool to measure the color of fruits. The designed CVS consists of a 60x60x60 cm black mini photo studio; a pair 15 watt LED lighting, sony α6000 digital camera, a set of laptop and an image processing software applications. Image processing software was programmed using VB.Net 2008 programming language. The developed CVS was calibrated using 24 color charts Macbeth Colorchecker (Gretag-Macbeth, USA). The calibration results of 24 color chart of Macbeth Colorchecker was resulted in a MAPE (Mean Absolute Percentage Error) value of component R / Red = 0%; G / Green = 0% and B / Blue = 0,5%; with 99% accuracy rate. In color measurement, the developed CVS had a 95% accuracy rate.


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