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Papaya Maturity Classification in MATLAB Platform using Lab Method and DHT11 Sensor

机译:使用实验室方法和DHT11传感器MATLAB平台的木瓜成熟度分类

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In this paper, the researchers have developed an integrated device that is fast, user-friendly, and affordable. It will accurately determine the maturity level of papaya in order to know the days left for a papaya to reach its maximum ripeness. The study focuses on identifying the classification of papaya by getting the maturity level. Six maturity levels are introduced, namely RS1 – Completely Green, RS2 – Distinct yellow at apex, RS3 – More green than yellow, RS4 – More yellow than green, RS5 – Tinge of green, and RS6 – Yellow / Yellow Orange. MATLAB is used for image processing. The method involves the segmenting of image and Detecting of Color which uses Clustering Based Techniques and LAB Method. Through a series of testing, the researchers were able to design a system that has an 86.67% accuracy in identifying the maturity level of papaya and an 86.67% accuracy in determining the number of days before the papaya becomes overripe. The design project has an average time of 8.11 seconds from the input to output process.
机译:在本文中,研究人员开发了一种快速,用户友好和实惠的集成设备。它将准确地确定木瓜的到期水平,以了解留下木瓜达到其最大成熟的日子。该研究侧重于通过获得到期水平来确定番木瓜的分类。介绍了六种成熟度水平,即RS1 - 完全绿色,Apex的rs2 - 不同的黄色,RS3 - 比黄色更大,Rs4更大,比绿色,Rs5 - 绿色,Rs6 - 黄色/黄色橙色。 MATLAB用于图像处理。该方法涉及图像和检测使用基于聚类技术和实验方法的颜色的分割。通过一系列测试,研究人员能够设计一个系统,在确定木瓜的成熟程度和86.67%的准确性方面的准确性,在番木瓜变成覆盖前的天数时,可以设计86.67%的精度。设计项目与输入到输出过程的平均时间为8.11秒。

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