本文選題：斑點落葉病 + 花葉病��； 參考：《西北農(nóng)林科技大學(xué)》2017年碩士論文

【摘要】：隨著蘋果種植面積的逐漸增大,果樹病害種類隨之增多,在某種程度上就有可能導(dǎo)致蘋果產(chǎn)成率的降低,從而會影響到果農(nóng)的經(jīng)濟收益。為解決此問題,實驗利用目前比較成熟的圖像處理技術(shù)和自動識別技術(shù)來實現(xiàn)陜西關(guān)中地區(qū)蘋果葉片各種病害的識別。本文介紹利用圖像處理技術(shù)自動檢測和識別蘋果葉片病害的方法,優(yōu)化病害圖像預(yù)處理算法,并針對圖像分割及模式識別部分算法開展研究。為避免在圖像處理過程中受葉片背景影響,采用基于灰度形態(tài)學(xué)圖像平滑方法。通過比較不同的圖像分割算法,對分割后得到的病斑或病斑輪廓進行特征提取,找出最能代表病斑特征的數(shù)據(jù),然后利用模式識別的方法來識別蘋果葉片病斑的種類和名稱。從病害的種類和性質(zhì)上來說,斑點落葉病、銹病、花葉病是陜西關(guān)中區(qū)域較為普遍的果樹病害,因此本文以此為研究對象,分析并提取其特征參數(shù),同時,設(shè)計相應(yīng)的蘋果葉片病害識別系統(tǒng)。本課題內(nèi)容主要包括以下幾點:(1)收集蘋果葉片斑點落葉病、銹病、花葉病3種病害圖像,并對所有的病害圖像進行圖像增強、去噪等預(yù)處理操作。(2)對預(yù)處理后的圖像進行圖像分割操作,從多種蘋果葉片圖像中分離病斑圖像,并提取出不同病斑的相關(guān)特征參數(shù)。(3)通過基于決策理論的模式識別方法對3種蘋果葉片病害圖像進行較為準確的識別。(4)設(shè)計蘋果葉片病害識別系統(tǒng)。本文設(shè)計出一種基于MATLAB的蘋果葉片病害識別系統(tǒng),能夠應(yīng)用于生產(chǎn)實踐中,使蘋果葉片病害識別技術(shù)較好地服務(wù)于廣大果農(nóng)。
[Abstract]:With the increase of apple planting area, the variety of fruit diseases will increase, which may lead to the decrease of apple yield to some extent, which will affect the economic benefits of fruit farmers. In order to solve this problem, the current mature image processing technology and automatic recognition technology are used to realize the identification of apple leaf diseases in Guanzhong area of Shaanxi Province. In this paper, the method of automatically detecting and recognizing apple leaf diseases by image processing technology is introduced, and the image preprocessing algorithm is optimized, and some algorithms of image segmentation and pattern recognition are studied. In order to avoid the influence of leaf background in image processing, a grayscale morphological image smoothing method is adopted. By comparing different image segmentation algorithms, the feature extraction of the disease-spot or disease-spot contour was carried out, and the most representative data was found, and then the type and name of the disease spot in apple leaf was identified by pattern recognition. As far as the species and properties of the disease are concerned, spot leaf disease, rust disease and mosaic disease are common diseases of fruit trees in Guanzhong region of Shaanxi Province. Therefore, this paper takes this disease as the research object, analyzes and extracts its characteristic parameters, at the same time, The corresponding apple leaf disease recognition system was designed. The main contents of this paper include the following points: 1) collect the three disease images of apple leaf spot, rust and mosaic, and enhance all the disease images. Pre-processing operations such as de-noising. 2) segmenting images after preprocessing and separating diseased images from a variety of apple leaf images. The relative characteristic parameters of different disease spots were extracted. (3) the apple leaf disease recognition system was designed by using the pattern recognition method based on the decision theory to identify the three apple leaf disease images accurately. In this paper, an apple leaf disease identification system based on MATLAB is designed, which can be applied to the production practice and make the apple leaf disease identification technology better serve for the majority of fruit farmers.
【學(xué)位授予單位】：西北農(nóng)林科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S436.611;TP391.41

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