Machine Vision based Quality Analysis of Rice Grains

被引：0

作者：

Devi, T. Gayathri ^{[1
]}

Neelamegam, P. ^{[2
]}

Sudha, S. ^{[1
]}

机构：

[1] SASTRA Univ, ECE, Sch EEE, SRC, Thanjavur, Tamil Nadu, India

[2] SASTRA Univ, E&I, Sch EEE, Thanjavur, Tamil Nadu, India

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON POWER, CONTROL, SIGNALS AND INSTRUMENTATION ENGINEERING (ICPCSI) | 2017年

关键词：

Quality assessment; grain properties; machine vision and grain grading;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

It is great challenge to meet the needs of quality assessment on rice grains. Testing on quality is gaining importance in food industry for classifying and grading the grains. Since manual testing is time consuming, costly and inaccurate, machine vision based quality analysis of rice grains is preferred. In machine vision based testing, we take both physical (grain shape and size) and chemical characteristics (amylose content, gel consistency) for evaluation and grading of rice grains. Quality assessment is done by finding 1) the region of boundary and 2) the end points of each grain by measuring the length, breadth and diagonal size of grain. In this proposed image processing algorithm, quality and grading of rice grains were analysed using the average values of the features extracted and it was implemented in Mat Lab.

引用

页码：1052 / 1055

页数：4