Intelligent identification of the seeds of Cyclocodon lancifolius,Campanumoea ja-vanica and Campanumoea javanica subsp.javanica based on multi-characteristic fusion in complex frequency domain
In order to improve the classification accuracy of the seeds of Cyclocodon lancifolius,Campanumoea ja-vanica and Campanumoea javanica subsp.javanica,a recognition algorithm based on multi-characteristic fusion in complex frequency domain and spatial domain was proposed.Firstly,stereoscopic microscopic images of the three kinds of seeds were taken.Secondly,the color features and directional gradient histogram features of the seed images were extracted in the spatial domain.Multi-scale and multi-direction complex frequency domain transformation of the images was carried out by using multi-directional dual tree complex wavelet transformation(M-DTCWT),and the shape features and texture features are extracted from the low-frequency sub-band images.Finally,ReliefF al-gorithm was used to fuse the spatial domain features and complex frequency domain features,and three classifiers(SVM,BPNN and RF)were used to realize the classification and recognition of the three kinds of seeds.The best classifier was determined and cross validation was conducted.The highest recognition rate of SVM was 98.67％,BPNN was 94.33％,RF was 99.67％,and RF cross-validation was 99.93％.The method could significantly im-prove the accuracy in the recognition of the three kinds of seeds.
万方数据
维普
