基于生豬外形特征圖像的瘦肉率估測方法
發(fā)布時間：2018-11-12 08:23
【摘要】：為實現(xiàn)生豬瘦肉率的快速無損檢測,以機(jī)器視覺為主要技術(shù),通過生豬的外形特征圖像進(jìn)行瘦肉率估測,為飼養(yǎng)者與收購者提供生豬品級的決策依據(jù)。采用MATLAB為開發(fā)工具,通過圖形用戶界面(graphical user interface,GUI)實現(xiàn)軟件操作界面,以生豬的側(cè)面及背面圖像為研究對象,利用圖像處理技術(shù)從目標(biāo)中提取體長、體高、胸深、腹長、臀寬、腰寬等數(shù)據(jù),以這些體尺的比例(胸深體高比、臀寬體長比、臀寬腰寬比、腹長體長比)為參數(shù),通過徑向基函數(shù)(radial basis function,RBF)神經(jīng)網(wǎng)絡(luò)進(jìn)行瘦肉率估測。該文分別對7組生豬外形圖像進(jìn)行處理,4項比例指標(biāo)的平均估測準(zhǔn)確率分別為92.90%、92.44%、95.17%、96.51%,瘦肉率的平均估測準(zhǔn)確率為94.35%。結(jié)果表明,該文所構(gòu)造的基于生豬外形特征圖像的瘦肉率估測方法工作效率高,成本低,可用于估測生豬瘦肉率。
[Abstract]:In order to realize the fast nondestructive testing of lean meat rate of live pigs, machine vision is used as the main technology to estimate the lean meat rate of live pigs by using the shape characteristic image of live pigs, which can provide the decision basis for pig quality grade for breeders and purchasers. Using MATLAB as the development tool, the software operation interface is realized through the graphical user interface (graphical user interface,GUI). The side and back images of the pig are taken as the research object, and the body length, body height, chest depth and abdomen length are extracted from the target by image processing technology. Based on the data of hip width, waist width and so on, the lean meat rate was estimated by radial basis function (radial basis function,RBF) neural network based on the ratio of breast depth to body height, hip width to body length, hip width to waist-width ratio and abdomen length to width ratio. In this paper, the contour images of 7 groups of live pigs were processed. The average accuracy of the four indexes was 92.90 and 95.179.179.51, respectively, and the average accuracy of the lean meat rate was 94.355.The average estimation accuracy of the four indexes was 92.90 and 95.179.51, respectively. The results show that the proposed method based on pig shape feature image has high efficiency and low cost and can be used to estimate lean meat rate of live pigs.
【作者單位】： 華南農(nóng)業(yè)大學(xué)工程學(xué)院/教育部南方農(nóng)業(yè)機(jī)械與裝備關(guān)鍵技術(shù)重點實驗室/廣東省食品質(zhì)量安全重點實驗室;安徽省農(nóng)業(yè)科學(xué)院農(nóng)業(yè)經(jīng)濟(jì)與信息研究所;
【基金】：廣東省科技計劃項目(2012A020602039) 廣州市產(chǎn)學(xué)研協(xié)同創(chuàng)新重大專項(201508010013)
【分類號】：TP391.41;TS251.51
本文編號：2326590
[Abstract]:In order to realize the fast nondestructive testing of lean meat rate of live pigs, machine vision is used as the main technology to estimate the lean meat rate of live pigs by using the shape characteristic image of live pigs, which can provide the decision basis for pig quality grade for breeders and purchasers. Using MATLAB as the development tool, the software operation interface is realized through the graphical user interface (graphical user interface,GUI). The side and back images of the pig are taken as the research object, and the body length, body height, chest depth and abdomen length are extracted from the target by image processing technology. Based on the data of hip width, waist width and so on, the lean meat rate was estimated by radial basis function (radial basis function,RBF) neural network based on the ratio of breast depth to body height, hip width to body length, hip width to waist-width ratio and abdomen length to width ratio. In this paper, the contour images of 7 groups of live pigs were processed. The average accuracy of the four indexes was 92.90 and 95.179.179.51, respectively, and the average accuracy of the lean meat rate was 94.355.The average estimation accuracy of the four indexes was 92.90 and 95.179.51, respectively. The results show that the proposed method based on pig shape feature image has high efficiency and low cost and can be used to estimate lean meat rate of live pigs.
【作者單位】： 華南農(nóng)業(yè)大學(xué)工程學(xué)院/教育部南方農(nóng)業(yè)機(jī)械與裝備關(guān)鍵技術(shù)重點實驗室/廣東省食品質(zhì)量安全重點實驗室;安徽省農(nóng)業(yè)科學(xué)院農(nóng)業(yè)經(jīng)濟(jì)與信息研究所;
【基金】：廣東省科技計劃項目(2012A020602039) 廣州市產(chǎn)學(xué)研協(xié)同創(chuàng)新重大專項(201508010013)
【分類號】：TP391.41;TS251.51
【相似文獻(xiàn)】
相關(guān)期刊論文 前2條
1 王曉軍;;中等徑級杉樹原木的制材——不同外形特征原木的下鋸方法及其出材率[J];國外林業(yè);1991年03期
2 ;[J];;年期
相關(guān)重要報紙文章 前2條
1 常麗君;基因位置對生物進(jìn)化影響更大[N];科技日報;2010年
2 ;喂養(yǎng)動物和種植花草[N];中國教育資訊報;2002年
相關(guān)碩士學(xué)位論文 前1條
1 吳權(quán)石;基于知識的飛機(jī)外形特征參數(shù)化設(shè)計[D];南昌航空大學(xué);2014年
，本文編號：2326590
本文鏈接：http://www.lk138.cn/kejilunwen/ruanjiangongchenglunwen/2326590.html
最近更新
教材專著
