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基于K均值聚類的綠色蘋果識別技
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Algorithm for Green Apples Recognition Based on K-means Algorithm
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    摘要:

    針對顏色和背景相近的綠色蘋果，提出了一種基于K-均值聚類的蘋果圖像識別算法。該算法以8×8像素的正方形區(qū)域為分割單位。選擇顏色差R-B作為顏色特征，選擇灰度均值m，標(biāo)準(zhǔn)偏差σ和熵e作為紋理特征，形成特征向量空間。采用間隙統(tǒng)計法確定蘋果圖像的最佳聚類數(shù)。 將特征向量空間和最佳聚類數(shù)作為輸入，運(yùn)用本文算法對蘋果圖像進(jìn)行聚類和分割。對200幅圖像識別實驗結(jié)果表明，在順光和逆光情況下，算法均能實現(xiàn)果實與背景的有效分割，果實識別的正確率高于

    Abstract:

    81%。 An apple recognition method based on K-means algorithm is proposed for the green apples that have similar color with leaves. The image is divided into 8×8 pixel blocks and the block is taken as the segmentation unit by the algorithm. Color difference R-B was selected as color feature and mean value, standard deviation and regional entropy of gray scale images are selected as texture features. The feature vectors including color feature and texture features are extracted. Gap statistic is applied to calculate the best number of the clusters. The recognition experiment is conducted to test the algorithm with 200 sample images taken in different illumination conditions. The experimental results show that the apple fruits can be recognized successfully both in front light conditions and back light conditions. The recognition rate reaches 81%.

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司永勝,劉剛,高瑞.基于K均值聚類的綠色蘋果識別技[J].農(nóng)業(yè)機(jī)械學(xué)報,2009,40(Z1):100-104. Algorithm for Green Apples Recognition Based on K-means Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(Z1):100-104.

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