Image processing methods to evaluate tomato and zucchini damage in post-harvest stages
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Álvarez Bermejo, José Antonio; Giagnocavo, Cynthia Lynn; Ming, Li; Castillo-Morales, Encarnacion; Morales Santos, Diego Pedro; [et al.]Fecha
2017Resumen
Through the supply chain, the quality or quality change of the products can generate important losses. The quality control in some steps is made manually that supposes a high level of subjectivity, controlling the quality and its evolution using automatic systems can suppose a reduction of the losses. Testing some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this study. Two steps in the supply chain are considered, the feeding of the raw products into the handling chain (because low quality generates a reduction of the chain productivity) and the cool storage of the processed products (as the value at the market is reduced). It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products (corresponding to specific farmers/suppliers, it should be asked to improve to maintain the productivity of the line). The second stage is analyzing the evolution of the p...
Palabra/s clave
image processing
color space
smartphone
efficient stitching
homography
controlled supervision
artificial vision
embedded parallel processing
injury assessment
traceability
post-harvest control
feature detection