Compare and analysis of detection algorithm of crop leaf area based on MATLAB software
dc.contributor.author | Chen Jie | |
dc.date.accessioned | 2020-03-27T08:36:48Z | |
dc.date.available | 2020-03-27T08:36:48Z | |
dc.date.issued | 2018 | |
dc.description.abstract | Traditional edge detection operators belong to linear filtering methods. Mathematical morphology is a non-linear filtering method, which can maintain the basic shape characteristics of the image and is widely used in various fields of image processing. Only the edge detection operator or mathematical morphology processing can’t get ideal segmentation results. According to the results of edge operator detection, morphological filtering and mathematical morphological operation are carried out, and the edge information of plant leaves is extracted by repeated experiments with different structural elements. Based on MATLAB software, the image of plant leaf was analysed by the diffent mathod of Sobel, Prewitt, Canny, and Morphology. The result of Sobel mathod as the best one was chosen to be analysed by Denoising mathod. The last result was suitable for the image area algorithm. | uk_UA |
dc.identifier.citation | Jie Chen . Compare and analysis of detection algorithm of crop leaf area based on MATLAB software / Chen Jie // Управління розвитком складних систем : зб. наук. праць / Київ. нац. ун-т буд-ва і архітектури ; гол. ред. Лізунов П. П. – Київ : КНУБА, 2018. – № 36. – С. 126-129. - Бібліогр. : 16 назв. | uk_UA |
dc.identifier.issn | 2219-5300 | |
dc.identifier.uri | https://repositary.knuba.edu.ua/handle/987654321/1937 | |
dc.language.iso | en | uk_UA |
dc.publisher | КНУБА | uk_UA |
dc.subject | Sobel mathod | uk_UA |
dc.subject | Prewitt mathod | uk_UA |
dc.subject | Canny mathod | uk_UA |
dc.subject | Morphology mathod | uk_UA |
dc.subject | Denoising method | uk_UA |
dc.subject.udc | 004.42 | uk_UA |
dc.subject.udc | 004.92 | uk_UA |
dc.title | Compare and analysis of detection algorithm of crop leaf area based on MATLAB software | uk_UA |
dc.type | Article | uk_UA |
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