Development of colour co-occurrence matrix (CCM) texture analysis for biosensing
Y Hendrawan, MR Fauzi, NS Khoirunnisa…�- …�Series: Earth and�…, 2019 - iopscience.iop.org
IOP Conference Series: Earth and Environmental Science, 2019•iopscience.iop.org
In various studies on pattern recognition using image analysis, many researchers used gray-
level co-occurrence matrix (GLCM) texture analysis. In this study, a colour-based texture
analysis software was developed based on colour co-occurrence matrix (CCM) to be
applied as bio-product sensing. CCM involves various colour space ie RGB, gray, HSV,
HSL, Lab, Luv, LCH, XYZ, CMY and CMYK. The CCM texture analysis software has been
tested successfully in four cases of bio-product sensing ie instant gatotqualityclassification;�…
level co-occurrence matrix (GLCM) texture analysis. In this study, a colour-based texture
analysis software was developed based on colour co-occurrence matrix (CCM) to be
applied as bio-product sensing. CCM involves various colour space ie RGB, gray, HSV,
HSL, Lab, Luv, LCH, XYZ, CMY and CMYK. The CCM texture analysis software has been
tested successfully in four cases of bio-product sensing ie instant gatotqualityclassification;�…
Abstract
In various studies on pattern recognition using image analysis, many researchers used gray-level co-occurrence matrix (GLCM) texture analysis. In this study, a colour-based texture analysis software was developed based on colour co-occurrence matrix (CCM) to be applied as bio-product sensing. CCM involves various colour space ie RGB, gray, HSV, HSL, Lab, Luv, LCH, XYZ, CMY and CMYK. The CCM texture analysis software has been tested successfully in four cases of bio-product sensing ie instant gatotqualityclassification; coffee type classification; tofu quality classification; and tempequalityclassification. The results obtained showed that CCM texture analysis software has a good performance to be implemented for biosensing.
iopscience.iop.org