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基于為害狀色相多重分形的椪柑病蟲害圖像識別
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湖南省科技計劃資助項目(2011NK3005、2012NK4127)


Damage Pattern Recognition of Citrus reticulate Blanco Based on Multi-fractal Analysis of Image Hue
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    摘要:

    為自動識別椪柑病蟲害,研究了以椪柑病蟲害為害狀多重分形譜特性參數(shù)為輸入變量的小波神經(jīng)網(wǎng)絡(luò)病蟲害識別方法。利用改進型分水嶺算法提取椪柑病蟲害為害狀邊界,對非連續(xù)的邊界進行邊界跟蹤,將過分割區(qū)域進行區(qū)域合并,標記為害狀邊界,提取標記區(qū)域,生成病蟲害為害狀目標圖像;對病蟲害為害狀目標圖像0°~120°這一主要色相區(qū)域4等分,產(chǎn)生4幅色相二值圖像;對二值圖像進行多重分形分析,計算其標度不變區(qū)多重分形譜的高度及寬度;以此高度及寬度作為小波神經(jīng)網(wǎng)絡(luò)的輸入,進行椪柑病蟲害識別,5種病蟲害的平均識別正確率為87%。試驗結(jié)果表明:椪柑病蟲害為害狀的4對多重分形譜高度及寬度值較充分地反映了椪柑病蟲害色相累計信息、分布信息及區(qū)間形狀的典型特征,能用此方法進行椪柑病蟲害機器識別。

    Abstract:

    The investigation proposed a new algorithm to automatize the identification process of pests and insects disease of Citrus reticulata Blanco var. Ponkan, in which multi-fractal spectra of image hue were set as inputs of wavelet neural network model. In the new algorithm, image boundary of damage pattern of Ponkan was extracted with improved watershed algorithm, and discontinuous boundary was processed with boundary following, meanwhile over-segmentation region was merged and boundary was marked, at last, damage pattern image was generated. After the work above, firstly, hue range 0°~120° of damage pattern image was equally segmented into 4 regions to generate 4 binary images. And then these binary images were analyzed by multi-fractal method to calculate the widths and heights of multi-fractal spectra of scale invariance region. In the end, the widths and heights of multi-fractal spectra were set as the inputs of wavelet neural network model to identify the pest and insects disease of citrus fruit. Test results showed that the accurate rate of identification of 5 pests and insects disease is about 87%, which means that widths and heights of multi-fractal spectra are sufficient to characterize the damage pattern of citrus fruit, and this method is applicable in machine automatic recognition for pests and insects disease of citrus fruit.

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溫芝元,曹樂平.基于為害狀色相多重分形的椪柑病蟲害圖像識別[J].農(nóng)業(yè)機械學報,2014,45(3):262-267. Wen Zhiyuan, Cao Leping. Damage Pattern Recognition of Citrus reticulate Blanco Based on Multi-fractal Analysis of Image Hue[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(3):262-267.

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  • 收稿日期:2013-03-15
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  • 在線發(fā)布日期: 2014-03-10
  • 出版日期: 2014-02-10