The present work demonstrates the implementation of image processing techniques to analyze the color and texture of agroindustrial products, in this case, of the piloncillo or panela in its granular and cone variety. A technological tool based on software was developed, capable of quantifying color and texture and thus implementing quality controls to support the commercialization of this product made in Huasteca Potosina towards global markets. An unsupervised classification method (clustering) is proposed to define the color or colors of the piloncillo, called K-means. In the case of texture analysis, second-order statistical methods derived from the co-occurrence matrix and six Haralick textural descriptors are used: contrast, homogeneity, energy, ASM, correlation and dissimilarity. The developed prototype was validated in 24 producing communities of granulated and cone-shaped piloncillo belonging to the municipalities of Tanlajas and Tancanhuitz, S.L.P. The results of the analysis of color and texture have been related to the manufacturing methods that are currently used, to identify improvements that help standardize the production process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.