图像处理技术在赤潮生物自动识别中的应用
Image Processing for Automated Identification of Harmful Algae
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摘要: 根据赤潮生物显微图像的特点,研究图像的预处理、分割和特征提取的处理过程.通过与其他自动分割方法进行比较,证明采用二维最大熵法可以有效地进行赤潮生物图像的自动阈值分割,并结合轮廓分析法和纹理分析法对于赤潮生物图像进行特征提取.实验结论表明,与人工识别计数方式比对,识别符合率大于80%.Abstract: The pre-processing, segmentation and feature extraction of harmful algae from micro-image are presented. Theoretical analysis and experiment results show that 2D entropic threshold algorithm is capable of segmenting the harmful algae’s image effectively, as compared with other auto-segmentation methods. Mathematical morphology was applied to increase the veracity of feature extraction. Feature extraction and classification are accomplished by using the image edge and texture. Experiment result indicates that the classification accuracy is over 80%, as compared with the artificial identification.
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