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基于機器視覺的荔枝果實采摘時品質檢測技術
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國家自然科學基金資助項目(31201135)和國家星火計劃資助項目(2013GA780043)


Fruit Quality Detection Based on Machine Vision Technology when Picking Litchi
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    摘要:

    為了在荔枝采摘時實時判斷果實的品質狀態(tài),,通過分析自然環(huán)境中荔枝不同生長期的圖像,對荔枝果實未成熟,、成熟、成熟后外表腐爛變質的3種情況進行了圖像數(shù)據(jù)分析。選取了YCbCr顏色模型,,利用探索性分析法對荔枝不同部位,、不同光照、不同生長期的荔枝圖像的Cr分量進行了數(shù)據(jù)分析與統(tǒng)計,,確定了辨識荔枝果實未成熟與成熟的Cr分量的閾值范圍,;對于成熟的荔枝,采用邊緣提取與Hough圓擬合方法對其Cr分量圖進行處理,,標記出圖像的荔枝果實,,然后利用紋理統(tǒng)計法、顏色特征與果實不同部分面積比值相結合的方法進行果實變質的判斷,,最終實現(xiàn)了未成熟,、成熟以及腐爛變質的荔枝果實的視覺智能判斷,建立了荔枝果實品質辨識的智能系統(tǒng),。試驗結果表明,,辨識荔枝品質狀態(tài)的正確率達93%。

    Abstract:

    In order to judge fruit quality real timely, three conditions of litchi fruit, immature, mature and appearance rot after mature, were analyzed by using the fruit images of different growth periods in natural environment. The YCbCr color space model was selected and the exploratory analysis method was used to analyze and estimate the Cr component of litchi images of different parts, different illuminations and different growing periods, and the threshold ranges of Cr components of mature and immature litchi fruits was determined; for mature litchi, the fruit edge detection and Hough circle fitting processing were carried out on the Cr component diagram to mark litchi fruits. And then the texture statistics and the method that combining the color feature and area ratio of different parts of litchi fruit were used to judge litchi fruit deterioration. Finally, the vision intelligent judgment for the immature, mature and appearance rot of litchi fruit was realized and an intelligent system to identify litchi fruit quality was built. The test results show that the accuracy of identify litchi fruit quality is 93%.

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熊俊濤,鄒湘軍,劉 念,彭紅星,李錦鴻,林桂潮.基于機器視覺的荔枝果實采摘時品質檢測技術[J].農業(yè)機械學報,2014,45(7):54-60. Xiong Juntao, Zou Xiangjun, Liu Nian, Peng Hongxing, Li Jinhong, Lin Guichao. Fruit Quality Detection Based on Machine Vision Technology when Picking Litchi[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(7):54-60.

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  • 收稿日期:2014-01-22
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  • 在線發(fā)布日期: 2014-07-10
  • 出版日期: 2014-07-10
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