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基于小波變換及Otsu分割的農(nóng)田作物行提取

韓永華,  汪亞明,  孫麒,  趙勻

韓永華, 汪亞明, 孫麒, 趙勻. 基于小波變換及Otsu分割的農(nóng)田作物行提取[J]. 電子與信息學(xué)報(bào), 2016, 38(1): 63-70. doi: 10.11999/JEIT150421
引用本文: 韓永華, 汪亞明, 孫麒, 趙勻. 基于小波變換及Otsu分割的農(nóng)田作物行提取[J]. 電子與信息學(xué)報(bào), 2016, 38(1): 63-70. doi: 10.11999/JEIT150421
HAN Yonghua, WANG Yaming, SUN Qi, ZHAO Yun. Crop Row Detection Based on Wavelet Transformation and Otsu Segmentation Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(1): 63-70. doi: 10.11999/JEIT150421
Citation: HAN Yonghua, WANG Yaming, SUN Qi, ZHAO Yun. Crop Row Detection Based on Wavelet Transformation and Otsu Segmentation Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(1): 63-70. doi: 10.11999/JEIT150421

基于小波變換及Otsu分割的農(nóng)田作物行提取

doi: 10.11999/JEIT150421 cstr: 32379.14.JEIT150421
  • 1.

    (浙江理工大學(xué)信息學(xué)院 杭州 310018) ②(浙江理工大學(xué)機(jī)械與自動(dòng)控制學(xué)院 杭州 310018)

基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61272311)，浙江省自然科學(xué)基金重點(diǎn)項(xiàng)目(LZ15F020004)，機(jī)械工程浙江省高校重中之重學(xué)科和浙江理工大學(xué)重點(diǎn)實(shí)驗(yàn)室優(yōu)秀青年人才培養(yǎng)基金(ZSTUME01B17)，計(jì)算機(jī)應(yīng)用創(chuàng)新重點(diǎn)學(xué)科研究生創(chuàng)新研究項(xiàng)目(XDY14003)，浙江理工大學(xué)科研啟動(dòng)基金(13032156-Y)，浙江理工大學(xué)521資助計(jì)劃項(xiàng)目

Crop Row Detection Based on Wavelet Transformation and Otsu Segmentation Algorithm

  • 1.

    (Department of Electronics and Informatics, Zhejiang Sci-Tech University, Hangzhou 310018, China)

  • 2.

    (Department of Electronics and Informatics, Zhejiang Sci-Tech University, Hangzhou 310018, China)

Funds: 

The National Natural Science Foundation of China (61272311), Zhejiang Provincial Natural Science Foundation (LZ15F020004), The Young Researchers Foundation of Zhejiang Provincial Top Key Academic Discipline of Mechanical Engineering and Zhejiang Sci-Tech University Key Laboratory (ZSTUME 01B17), Graduate Student Innovation Research Project of Computer Application Innovation Key Subject (XDY14003), Science Foundation of Zhejiang Sci-Tech University (ZSTU) (13032156-Y), 521 Project of Zhejiang Sci-Tech University

  • 摘要: 基于機(jī)器視覺的田間車輛自動(dòng)導(dǎo)航是農(nóng)用車輛導(dǎo)航的熱門研究方向，但含較密集雜草的農(nóng)田作物行提取，目前依然是個(gè)難題。該文提出一種適用于密集雜草農(nóng)田的，主要基于頻率和顏色信息的農(nóng)田圖像分割算法。通過小波多分辨率分解后構(gòu)建的頻率總量指標(biāo)，利用作物產(chǎn)生主頻信息的總量?jī)?yōu)勢(shì)，結(jié)合作物行的交替及最大類間方差法、顏色模型分量變換，實(shí)現(xiàn)農(nóng)田雜草的去除，并通過最小二乘法擬合直線，實(shí)現(xiàn)農(nóng)田作物行提取。實(shí)驗(yàn)表明算法能有效克服密集雜草干擾，針對(duì) 像素大小圖像，單幅處理時(shí)間平均為132 ms。
    Abstract: Vision-based agricultural vehicle navigation has become a popular research area of automated guidance, however, crop row detection in high weeds field is still a challenging topic. An image segmentation method mainly based on frequency and color information is proposed to remove weeds. The algorithm is based on total frequency parameters, more total crop frequency, alternation regular of crop rows, Otsu method and color model transformation. The total frequency parameters are obtained from wavelet multi-resolution decomposition. The least square method is used in fitting straight line to detect the crop rows. Experiments show that the algorithm can effectively overcome the high weeds. The average processing time of a single pixels image is 132 ms.
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出版歷程
  • 收稿日期:  2015-04-10
  • 修回日期:  2015-09-13
  • 刊出日期:  2016-01-19

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