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江苏科技大学毕业设计规范

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精品 江苏科技大学

本 科 毕 业 设 计(论文)

学 院 电子信息学院

专 业 电气工程及其自动化

学生姓名 杨炎平

班级学号 1040304228

指导教师 庄肖波

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精品 二零一四年六月

江苏科技大学本科毕业论文

水稻产量估算系统设计

Rice yield estimation system design

摘要

水稻是我国最重要的食物之一,在这个人口迅速增长的基本国情之下,一个高效的、可推广的水稻估产方法是了解水稻产业的基本保证。虽然现在国际上对于水稻产量有不少的研究,个别方法已经在实际应用中。不过很多方法并不能得到广泛的使用,因为这些估产方法普遍存在人力、物力需求太大,受天气影响较大,数据采集和处理过于复杂等问题。因此,目前研究出一种简单、方便、大众化的水稻估产方法显得尤为重要。

本文通过研究目前的一些水稻估产方法,根据图象纹理分析、分形理论以及多元线性回归来建立水稻产量模型。

1. 在学习了目前水稻估产方法的优缺点后,选择成熟期的水稻作为研究对象,进行进一步处理,来估算水稻产量。相比之下此方法需要更少的人力、物力,而且更加简单、精确,为以后研究水稻产量打下一定的基础。

2. 获取成熟期水稻的稻穗图像以及单位面积的水稻图像。通过图像处理软件,先对图像灰度化处理后再进行二值化分割等。在分形理论的基础下,进行纹理分析,提取水稻的特征参数。由主成分分析法分析各特征参数,提取出关键的特征参数。可编辑

精品 3. 分析水稻特征参数跟水稻产量之间的关系,通过多元线性回归建立水稻产量模型。稻穗产量模型:Y=5.717-0.367z1,Y表示的是稻穗的质量,z1表示的是稻穗的主成分。单位面积水稻产量模型:Y=0.789+0.059z1+0.029z2+0.054z3,Y表示一个平方的水稻产量,z1、 z1、 z3表示单位面积水稻产量的主成分。

4. 本文采用一种新的思路,通过摄取图像,分析处理,建立模型来估算水稻产量。在后期的研究中,可以在联合收割机上安装摄像头,获取水稻图像,进行实时实地的验证研究。

关键字:水稻、产量、分形、建模

Rice is one of the country's most important food in this rapid

population growth under the basic conditions of, an effective, replicable

methods of rice yield estimation is to understand the fundamental

guarantees of the rice industry. Now many studies on rice yield,

individual approach has practical applications. Though many methods

cannot be widely used, since these methods of estimation demand widespread

human, material is too large, more affected by the weather, and issues

such as data collection and processing is too complex. Therefore,

developed a simple, convenient and popular rice yield estimation method

is particularly important. By studying the current rice yield estimation

methods in this article, based on image texture analysis, fractal theory

to establish rice yield and multiple linear regression models.

1.After learning the strengths and weaknesses of current rice yield

estimation methods, select maturity of rice as a research object for

further processing, to estimate rice yields. In contrast this method

requires less manpower and resources, and more simple, precise, and

studies on rice yield and lay a foundation for the future.可编辑

精品 2.Get mature rice grain image and the image of rice per unit area.

Image processing software, image processing and binarization

segmentation again. On the basis of fractal theory, texture analysis,

extraction of characteristic parameters of rice. By principal component

analysis analysis feature parameters, extract critical parameters.

3.Analysis of relationship between characteristic parameters of

paddy rice production, rice production in established through multiple

linear regression models. Rice production model: Y=5.717-0.367z1,Y the

quality of rice, Z1 is the principal component of rice. Rice yield per

unit area model: Y=0.789+0.059z1+0.029z2+0.054z3,Y that a square of rice

yield, Z1, Z1, Z3 is a principal component of rice yield per unit area.

In this paper, a new way of thinking, by taking the image, analytical

processing, modelling to estimate rice yields. In the latter part of the

study, you can combine a camera installed, gets paddy image, real-time

validation studies in the field.

Keywords: rice, grain yield, fractal, modeling

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目录

第一章 绪论 .................................................................................................................................... 8

1.1背景与意义 ........................................................................................................................ 8

1.2国内外研究现状................................................................................................................. 9

1.3水稻估产方法 .................................................................................................................. 10

1.3.1 田间测产 .............................................................................................................. 10

1.3.2 遥感估产 .............................................................................................................. 10

1.3.3 作物环境模型....................................................................................................... 11

1.4研究内容与思想............................................................................................................... 11

第二章 水稻穗头图像纹理和分形特征分析 ............................................................................... 12

2.1图像处理 .......................................................................................................................... 14

2.1.1 灰度化处理 .......................................................................................................... 14

2.1.2 二值化处理 .......................................................................................................... 14

2.1.3 边缘检测 .............................................................................................................. 15

2.2水稻穗头分形分析........................................................................................................... 15

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