The aim of this research was to design, implement and calibrate a Computer Vision System (CVS), for use in real-time, in order to measure the color on minimally processed yacon slices. For this purpose, a device (software and hardware) was designed and implemented which consisted of two steps: a) image acquisition and b) image processing and analysis. For both, an algorithm and a graphical user interface (GUI) were developed in MatLab. CVS calibration was performed with a conventional colorimeter (Model CIE L*a*b*). Minimally processed yacon slices were obtained and stored at 5°C. Color changes were estimated every 2h, for 26h, obtaining its color parameters. L* decreased from 65.9 to 60.8, with a tendency to a black color; a* increased from 7.3 to 17.7, approaching a red color; b* increased from 35.1 to 41.5, presenting a tendency to a yellow color. Moreover, C* increased from 35.9 to 40.1, H* decreased from 78.2 to 66.9 and δE* increased from 2.6 to 13.2. Low errors calculated (eL*=5.001%, and ea*=2.287%, and eb*=4.314%) ensure suitable and efficient application in industrial process automation and quality control in the food industry. © 2014 Elsevier Ltd.