Assessment of Color Levels in Leaf Color Chart Using Smartphone Camera with Relative Calibration

by Yuita Arum Sari,R V Hari Ginardi,Riyanarto Sarno
( Department of Informatics Faculty of Information Technology Institut Teknologi Sepuluh Nopember )

Date Published: 02 Dec 2013
Published In: Information Systems International Conference (ISICO)
Volume: 2013
Publisher: Departemen Sistem Informasi, Institut Teknologi Sepuluh Nopember
Language: id-ID

Keywords: classification,Leaf Color Chart,Camera Calibration,Color Interpretation,KNN


Leaf Color Chart (LCC) is used in agriculture modeling for monitoring the plant performance by comparing the leaf color and its corresponding color in LCC. To digitize the acquisition and interpretation of leaf color, smartphone camera is used. A color calibration is necessary for a smartphone before it can be used to capture and interpret leaf color. The calibration process evaluates the camera performance with the operational lighting conditions and determine whether the smartphone camera can be used for leaf color interpretation or not. The result from camera color calibration is used as a relative color chart for interpreting leaf color. In this paper, we propose a method of relative color calibration, which makes the system, learns colors chart automatically without depending on specific standard colors. K-Nearest-Neighbor (KNN) classification is used for color learning process in RGB color space. Our method is sucessfully tested with two smartphone devices in different lighting condition. The test shows an average accuracy above the threshold value of 83%.

© 2023 Open Access Journal of Information Systems (OAJIS) | created by : radityo p.w ( and rully a.h (eraha99 [at]