Image Processing Techniques based Feature Extraction for Insect Damage Areas

نویسندگان

چکیده

Monitoring of forests is important for the diagnosis insect damage to vegetation. Detection and monitoring damaged areas facilitates control pests practitioners. For this purpose, Unmanned Aerial Vehicles (UAVs) have been recently used detect areas. In order distinguish from healthy on UAV images, it necessary extract feature parameters images. Therefore, extraction an step in Computer Aided Diagnosis monitored with By reducing size image data, possible between extracted features. The accuracy classification algorithm depends segmentation method Grey-Level Co-occurrence Matrix (GLCM) characterizes texture based number pixel pairs specific intensity values arranged spatial relationships. paper, characteristics were images using GLCM. 3000*4000 resolution containing larch trees analyzed Definiens Developer (e-Cognition software) multiresolution analysis, scale applied as 500, shape 0.1, color 0.9 compactness 0.5. As a result segmentation, GLCM homogeneity, contrast entropy calculated each segment. When calculating texturing parameters, neighborhoods different angular directions (0,45,90,135) are taken into account. calculations made by considering all directions, was found that homogeneity ranged 0.08 - 0.2, 82.86 303.58 7.81 8.51. On other hand, varies 0.05 0.08, 441.70 888.80 8.93 9.40. study demonstrated technique can be reliable detection imagery.

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ژورنال

عنوان ژورنال: European journal of forest engineering

سال: 2023

ISSN: ['2149-5637']

DOI: https://doi.org/10.33904/ejfe.1320121