Mushroom Image Classification Using C4.5 Algorithm

Cucut Hariz Pratomo, W. Andriyani
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Abstract

This study applied five types of Mushrooms, they are Button mushrooms, Wood Ear mushrooms, Straw mushrooms, Reishi mushrooms and Red Oyster mushrooms. The feature extraction used is Order 1 with the parameters of mean, skewness, variance, kurtosis, and entropy. The process carried out to identify mushroom images by preparing image objects. There were 15 images of each mushroom class were taken for each mushroom and stored in .jpg format. The image processing is carried out by a feature extraction process. Then five images for each mushroom class are chosen. They were used as test images which will be classified so that identification results are obtained. This study applies the Classification Algorithm C4.5 to build a decision tree, which will also identify the results of the accuracy of processed mushroom images. The obtained result of accuracy was 84% in the classification of feature extraction Order 1
基于C4.5算法的蘑菇图像分类
本研究使用了五种蘑菇,分别是钮子菇、木耳菇、草菇、灵芝菇和红平菇。使用的特征提取是Order 1,参数为均值、偏度、方差、峰度和熵。通过准备图像对象来识别蘑菇图像的过程。每个蘑菇类拍摄15张图片,保存在。jpg格式。通过特征提取过程对图像进行处理。然后为每个蘑菇类选择5张图片。将其作为测试图像进行分类,从而得到识别结果。本研究采用C4.5分类算法构建决策树,该决策树也将对处理后蘑菇图像的精度结果进行识别。在特征提取阶1的分类中,获得的准确率为84%
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