Determination of ripeness and grading of tomato using image analysis on Raspberry Pi

Ruchita R. Mhaski, P. B. Chopade, M. Dale
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引用次数: 31

Abstract

Fruits and vegetables market is subject of choice. Thus, it is important for the suppliers to label the quality of goods before dealing out. Some commercially available fruit sorting and grading system have been introduced, but they are almost expensive for small and medium fruit processing industry. Presently, human experts grade the agriculture goods based on its vision based features that cause the inaccuracy, inconsistency and inefficiency on defining the quality of agriculture goods. In this paper, we are inspecting the quality of tomato based on shape, size and degree of ripeness. An edge detection algorithm is used to estimate the shape and size of tomato and color detecting algorithm is used for the ripeness determination. All these algorithms are implemented on Raspberry Pi development board which will become independent and cost effective system. Our system includes Raspberry Pi development board, conveyor belt, motors, Pi camera. All the interfacing of the above devices will be carried out and will make a cost effective embedded system for the determination of shape, size and degree of ripeness of tomato. Same system can be utilized for other fruits and vegetables also.
树莓派图像分析测定番茄成熟度及分级
蔬果是市集的首选对象。因此,供应商在进行交易前对商品的质量进行标识是很重要的。市面上已有一些水果分选分级系统,但对于中小型水果加工业来说价格昂贵。目前,人类专家基于农产品的视觉特征对其进行分级,导致了农产品质量定义的不准确、不一致和低效率。本文从番茄的形状、大小和成熟度三个方面对番茄的质量进行了检验。用边缘检测算法估计番茄的形状和大小,用颜色检测算法确定成熟度。所有这些算法都在树莓派开发板上实现,将成为一个独立的、具有成本效益的系统。我们的系统包括树莓派开发板、传送带、电机、树莓派相机。上述设备的所有接口都将进行,并将制作一个具有成本效益的嵌入式系统,用于确定番茄的形状,大小和成熟度。同样的系统也可以用于其他水果和蔬菜。
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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