TY - JOUR
T1 - Color and Texture Analysis of Textiles Using Image Acquisition and Spectral Analysis in Calibrated Sphere Imaging System-I
AU - Rout, Nibedita
AU - Baciu, George
AU - Pattanaik, Priyabrata
AU - Nakkeeran, K.
AU - Khandual, Asimananda
N1 - Funding
This research received no external funding.
Acknowledgments
We are also grateful to Manas Sarkar, ITC, HKPU for providing cotton samples with varied textures and Dystar, Hong Kong, for generously providing us with dye samples. We are thankful to for the experimental support from new fiber science and IoT Lab, OUTR sponsored by TEQIP-3 seed money and MODROB (/9-34/RIFDMO DPOLICY-1/2018-19).
PY - 2022/11/24
Y1 - 2022/11/24
N2 - Numerous imaging applications and analyses demand human perception, and color space transformation of device-dependent tri-band color interpretation (RGB) to device-independent CIE color space standards needs human intervention. The imaging acquisition environment, theoretical conversion errors, viewing geometry, well-defined illumination uniformity, and calibration protocols limit their precision and applicability. It is unfortunate that in most image processing applications, the spectral data are either unavailable or immeasurable. This study is based on developing a novel integrating sphere imaging system and experimentation with textiles’ controlled variation of texture and color. It proposes a simple calibration technique and describes how unique digital color signatures can be derived from calibrated RGB derivatives to extract the best features for color and texture. Additionally, an alter-ego of reflectance function, missing in the imaging domain, is suggested that could be helpful for visualization, identification, and application for qualitative and quantitative color-texture analysis. Our further investigation revealed promising colorimetric results while validating color characterization and different color combinations over three textures.
AB - Numerous imaging applications and analyses demand human perception, and color space transformation of device-dependent tri-band color interpretation (RGB) to device-independent CIE color space standards needs human intervention. The imaging acquisition environment, theoretical conversion errors, viewing geometry, well-defined illumination uniformity, and calibration protocols limit their precision and applicability. It is unfortunate that in most image processing applications, the spectral data are either unavailable or immeasurable. This study is based on developing a novel integrating sphere imaging system and experimentation with textiles’ controlled variation of texture and color. It proposes a simple calibration technique and describes how unique digital color signatures can be derived from calibrated RGB derivatives to extract the best features for color and texture. Additionally, an alter-ego of reflectance function, missing in the imaging domain, is suggested that could be helpful for visualization, identification, and application for qualitative and quantitative color-texture analysis. Our further investigation revealed promising colorimetric results while validating color characterization and different color combinations over three textures.
KW - computer vision
KW - CIE color space
KW - color image processing
KW - radiance
KW - tri-stimulus value
KW - d/80 geometry
KW - integrating sphere imaging
U2 - 10.3390/electronics11233887
DO - 10.3390/electronics11233887
M3 - Article
VL - 11
JO - Electronics (Switzerland)
JF - Electronics (Switzerland)
SN - 2079-9292
IS - 23
M1 - 3887
ER -