TY - JOUR
T1 - Image Processing Applied to Classification of Avocado Variety Hass (Persea americana Mill.) During the Ripening Process
AU - Arzate-Vázquez, Israel
AU - Chanona-Pérez, J. Jorge
AU - de Perea-Flores, María Jesús
AU - Calderón-Domínguez, Georgina
AU - Moreno-Armendáriz, Marco A.
AU - Calvo, Hiram
AU - Godoy-Calderón, Salvador
AU - Quevedo, Roberto
AU - Gutiérrez-López, Gustavo
N1 - Funding Information:
Acknowledgments Israel Arzate-Vázquez wishes to thanks CONACyT and PIFI-IPN-México for the scholarship provided. We want to thank the financial support of the Mexican Government (COFAA, EDI, and SIP of IPN, and CONACyT) to carry out this project.
PY - 2011/10
Y1 - 2011/10
N2 - This work was undertaken to analyze the ripening process of avocados variety Hass (Persea americana Mill.) by image processing (IP) methodology. A set of avocados (10 samples) was used to follow the changes in image features during ripening by applying a computer vision system, extracting color and textural parameters. Other 16 avocados were used to evaluate the firmness and mass loss. Three maturity stages of avocados were established, and a classification was obtained by applying principal component analysis and k-nearest neighbor algorithm. During the ripening process (12 days), avocado firmness decreased from 75.43 to 2.63 N, while skin color values kept invariable during 6 days after that, a decrement in the peel green color (a*) was observed (-9.68 to 2.32). Image features showed that during ripening the color parameters (L*, a*, and b*), entropy (4.29 to 4.00), angular second moment (0.287 to 0.360), and fractal dimension (2.58 to 2.44) had a similar path as compared to mass loss, a*, and firmness ripening parameters, respectively. Relationships between image features and ripening parameters were obtained. The parameter a* was the most useful digital feature to establish an acceptable percentage of avocado classification (>80%) in three different maturity stages found. Results obtained by means of IP could be useful to evaluate, at laboratory level, the ripening process of the avocados.
AB - This work was undertaken to analyze the ripening process of avocados variety Hass (Persea americana Mill.) by image processing (IP) methodology. A set of avocados (10 samples) was used to follow the changes in image features during ripening by applying a computer vision system, extracting color and textural parameters. Other 16 avocados were used to evaluate the firmness and mass loss. Three maturity stages of avocados were established, and a classification was obtained by applying principal component analysis and k-nearest neighbor algorithm. During the ripening process (12 days), avocado firmness decreased from 75.43 to 2.63 N, while skin color values kept invariable during 6 days after that, a decrement in the peel green color (a*) was observed (-9.68 to 2.32). Image features showed that during ripening the color parameters (L*, a*, and b*), entropy (4.29 to 4.00), angular second moment (0.287 to 0.360), and fractal dimension (2.58 to 2.44) had a similar path as compared to mass loss, a*, and firmness ripening parameters, respectively. Relationships between image features and ripening parameters were obtained. The parameter a* was the most useful digital feature to establish an acceptable percentage of avocado classification (>80%) in three different maturity stages found. Results obtained by means of IP could be useful to evaluate, at laboratory level, the ripening process of the avocados.
KW - Avocado
KW - Firmness
KW - Fractal dimension
KW - Image processing
KW - Ripening
UR - http://www.scopus.com/inward/record.url?scp=80051567024&partnerID=8YFLogxK
U2 - 10.1007/s11947-011-0595-6
DO - 10.1007/s11947-011-0595-6
M3 - Artículo
SN - 1935-5130
VL - 4
SP - 1307
EP - 1313
JO - Food and Bioprocess Technology
JF - Food and Bioprocess Technology
IS - 7
ER -