【摘要】：水稻是我國最主要的糧食作物,在農(nóng)業(yè)生產(chǎn)和糧食安全中具有關(guān)鍵性的作用。白背飛虱[Sogatellafurcifera(Horvath)]是目前影響水稻高產(chǎn)、穩(wěn)產(chǎn)的主要害蟲之一,因此,必須對白背飛虱種群數(shù)量進(jìn)行準(zhǔn)確的監(jiān)測和預(yù)測。根據(jù)植保專家和昆蟲學(xué)家的意見,通過量化白背飛虱背部幾何形態(tài)、顏色和紋理特征的方法,本文設(shè)計了一套基于圖像處理技術(shù)的白背飛虱智能識別系統(tǒng)。為了獲取清晰的白背飛虱昆蟲圖像,設(shè)計并搭建了野外昆蟲圖像采集裝置。采集裝置主要由采集裝置機(jī)械平臺、自動拍攝控制系統(tǒng)組成。采集裝置機(jī)械平臺由底座、采集工作臺和傳動系統(tǒng)組成。底座為1OOcm×100cm田字形框架,支撐整個實驗平臺;采集工作臺大小為120cm×90cm,放置白色幕布,為白背飛虱等昆蟲提供趴伏處;傳動系統(tǒng)負(fù)責(zé)帶動相機(jī)二維平面運(yùn)動。自動拍攝控制系統(tǒng)主要由拍攝系統(tǒng)和運(yùn)動控制系統(tǒng)組成。拍攝系統(tǒng)由相機(jī)、遠(yuǎn)心鏡頭、圖像采集卡和RI環(huán)形冷光源組成,負(fù)責(zé)拍攝清晰的白背飛虱圖像。運(yùn)動動控制系統(tǒng)主要由伺服電機(jī)、伺服驅(qū)動器和PLC組成。通過PLC輸出脈沖到伺服驅(qū)動器驅(qū)動伺服電機(jī),并帶動相機(jī)的X向和Y向的二維平面運(yùn)動,且觸發(fā)相機(jī)有序的掃描拍攝整個幕布,最終獲取自然狀態(tài)下的白背飛虱昆蟲圖片。用自制的野外昆蟲圖像采集裝置,在野外環(huán)境下,采集131張白背飛虱昆蟲圖像。通過顏色(藍(lán)色分量B=130)閾值分割、濾波處理后,獲取昆蟲圖像的二值化圖,然后提取出單個昆蟲背部區(qū)域二值化圖和背部區(qū)域灰度圖。對白背飛虱的大小和顏色成分進(jìn)行統(tǒng)計分析,剔去明顯非白背飛虱的單個昆蟲圖像,再運(yùn)用不變矩和二維傅里葉頻譜數(shù)據(jù)描述昆蟲幾何形態(tài)、顏色和紋理共88個特征,將7個不變矩和l×l(l=1,2,...,9)個二維傅里葉頻譜特征進(jìn)行組合并作為輸入變量,建立基于支持向量機(jī)的白背飛虱識別模型。實驗結(jié)果顯示白背飛虱樣本的正確識別率達(dá)到95%,表明該方法可以實現(xiàn)田間白背飛虱的自動識別。
[Abstract]:Rice is the most important food crop in China and plays a key role in agricultural production and food security. Sogatella furcifera (Horvath) is one of the main pests affecting the high and stable yield of rice. Therefore, it is necessary to accurately monitor and predict the population of the white-backed planthopper. In order to obtain a clear image of the white-backed planthopper, a field insect image acquisition device is designed and built. The acquisition device is mainly composed of acquisition device machinery. The mechanical platform of the acquisition device is composed of a base, a collection table and a transmission system. The base is an OOcm *100cm field-shaped frame, supporting the entire experimental platform. The size of the acquisition table is 120 cm *90cm, and a white screen is placed to provide a dormant place for insects such as white-backed planthopper. The transmission system is responsible for driving the camera 2. The system consists of a camera, telecentric lens, image acquisition card and RI ring cold light source. It is responsible for taking clear pictures of the white-backed planthopper. The motion control system is mainly composed of a servo motor, a servo driver and a PLC. The pulse is output by PLC. The servo driver drives the servo motor and drives the camera to move in X and Y directions in two-dimensional plane, and triggers the camera to scan and photograph the whole curtain orderly, and finally obtains pictures of the white-backed planthopper insects in the natural state. The color (blue component B = 130) threshold segmentation is used to obtain the binary image of the insect image after filtering. Then the binary image of the back region and the gray image of the back region of the single insect are extracted. The size and color components of the white-backed planthopper are statistically analyzed, and the single insect image with obvious non-white-backed planthopper is removed. Then the invariant moments and two-dimensional image are used. Fourier spectral data describe the geometry of insects. The color and texture of insects are 88 features. Seven moment invariants and l *l (l=1,2,..., 9) two-dimensional Fourier spectral features are combined as input variables to establish a white-backed planthopper identification model based on support vector machine. This method can automatically identify white backed planthopper in the field.
【學(xué)位授予單位】：南京農(nóng)業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP391.41;S435.112.3

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