PENGOLAHAN CITRA DIGITAL DAN LOGIKA FUZZY DALAM IDENTIFIKASI TINGKAT KEMATANGAN BUAH

Agus Suryadi, Meylia Vivi Putri, E. Febrianti
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引用次数: 1

Abstract

This study aims to implement digital image processing and fuzzy logic in identifying the maturity level of red dragon fruit and describing the level of accuracy. The process carried out is to change the type of red dragon fruit image from the red green blue (RGB) type to the grayscale type. Furthermore, extraction is carried out using MATLAB to obtain information from the image. Information from the image is contrast, correlation, energy, homogeneity, mean, variance, entropy. There are 7 information used as fuzzy input. The input fuzzy model uses triangular and trapezoidal membership functions to construct fuzzy rules on 28 data, so there are 28 fuzzy rules. After the fuzzy rules are obtained, then the inference and defuzzification processes are carried out. The inference used is the mamdani method. The result of defuzzification is the value for the maturity level of red dragon fruit which is divided into four categories, namely raw, half-ripe, ripe, rotten. The fuzzy model that has been built will test the model by determining the level of accuracy and error of the model. With the results of 96.42% with an error of 3.57%.
处理数字图像和模糊逻辑以确定水果的成熟度
本研究旨在将数位影像处理与模糊逻辑应用于红火果成熟度的辨识与准确度描述。所进行的过程是将红火果图像的类型由红绿蓝(RGB)类型变为灰度类型。然后利用MATLAB进行提取,从图像中获取信息。来自图像的信息是对比度、相关性、能量、同质性、平均值、方差和熵。有7个信息作为模糊输入。输入模糊模型采用三角形和梯形隶属函数对28个数据构建模糊规则,共28条模糊规则。在得到模糊规则后,进行推理和去模糊化处理。使用的推理是mamdani方法。去模糊化的结果就是红火果的成熟度值,红火果的成熟度分为生、半熟、熟、烂四类。已经建立的模糊模型将通过确定模型的精度和误差水平来检验模型。结果为96.42%,误差为3.57%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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