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oai:docta.ucm.es:20.500.14352/433212024-08-21T13:51:08Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense author Ribeiro, Angela author Ranz, Juan author Burgos Artizzu, Xavier Paolo author Pajares Martínsanz, Gonzalo author Sánchez del Arco, María author Navarrete, Luis 2023-06-20T01:07:17Z 2023-06-20T01:07:17Z 2011-06-17 1424-8220 10.3390/s110606480 https://hdl.handle.net/20.500.14352/43321 https://doi.org/10.3390/s110606480 https://www.mdpi.com/1424-8220/11/6/6480 Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantific depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).ation obtained using template images. Moreover, the proposed method does not. eng Atribución 3.0 España An Image Segmentation Based on a Genetic Algorithm for Determining Soil Coverage by Crop Residues journal article URL https://docta.ucm.es/bitstreams/024672c4-a5bc-4314-8f10-4f881c245b5f/download File MD5 78b6b6ee3f62d507bacd9158e35014b4 736549 application/pdf sensors-11-06480.pdf URL https://docta.ucm.es/bitstreams/a2cee970-be6d-42e4-ae7b-189cd6ed7def/download File MD5 c16dc407707818d2bfd5c82a7a5c226c 36021 text/plain sensors-11-06480.pdf.txt