自动水产养殖作业船的视觉导航技术研究.doc
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自动水产养殖作业船的视觉导航技术研究, 1.85万字自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用 摘要 数字图像处理就是利用计算机对图像信息进行加工，以满足人的视觉心理或者应用的需求。图像识别所讨论的问题，是研究用计算机代替人自动地处理大量的物理信息，解决人类所不能识别的问题。对于计算机来说，在实际工作环...
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自动水产养殖作业船的视觉导航技术研究
1.85万字
自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用
摘要 数字图像处理就是利用计算机对图像信息进行加工，以满足人的视觉心理或者应用的需求。图像识别所讨论的问题，是研究用计算机代替人自动地处理大量的物理信息，解决人类所不能识别的问题。对于计算机来说，在实际工作环境里，图像场景已有较大的变化。因此要区分图像属于哪一类，往往要通过一系列关键技术来实现。由此产生的图像识别方法也有很多。
本文以水面障碍物目标（竹竿、渔网等）的图像识别为例，从白天自然光条件下的图像识别方法入手，展开研究。本文以数学图像处理为重点，较详细地论述了对水面上障碍物目标进行图像识别的技术和过程。由于采集到的图像目标和背景灰度色差不是很明显，对于的图像分割不适合采用色差分割法，于是，本文采用了边缘检测的方法进行识别。包括图像预处理、边缘提取、噪声去除、图像锐化和领域平均法处理等的主要过程。最终达到目标识别的目的。研究结论如下：
（1）灰度化处理使原来的彩色图像灰度化，并进行图像缩放以减少计算量，提高运算效率，对灰度图像进行边缘检测，滤波和锐化，突出目标，削弱背景噪声。
（2）采用邻域平均法对图像中的目标和远处水面背景噪声进行分割，提取出图像中的目标，为进一步得到目标的位置等信息打下基础。
本文在较广泛地调研文献的基础上，对图像识别系统进行了较为全面的综述，并以较为大量文字和具体的实例，通过使用常用的仿真语言和软件对基于数字图像处理的障碍物的识别进行了研究，获得了较理想的识别结果。
关键词： 图像处理 水面目标识别 边缘检测 视觉导航
Abstract Digital image processing is the use of computers for image information processing to meet the person's visual psychology or application requirements. Issues discussed at image recognition, is the study of automatically replace people use your computer to work with large amounts of physical information, solve the problem of human beings does not recognize. For the computer, in the actual working environment, image scene has a larger change. Therefore, to distinguish between images fall into which category, often through a series of key technology to achieve. The resulting image recognition also has many kinds of methods.
Based on the target surface obstacles (bamboo, fishing nets, etc.) of image recognition, for example, from the natural light during the day under the condition of image recognition method of study. Focusing on mathematical image processing, this paper discusses on the surface of the water obstacles target image recognition technology and process. Because of the collected image object and background gray color difference is not very obvious, for the image segmentation is not suitable for color segmentation method is used to, so, in this paper, the edge detection method was adopted for identification. Including image preprocessing, edge detection and noise removal and image sharpening and average method, the main process. Ultimately achieve the goal of target recognition. Research conclusions are as follows:
(1)Gray processing make the original color image gray level and image zooming to reduce the amount of calculation, improve the efficiency of operation, and the gray image edge detection, filtering and sharpening, highlight the objectives and weaken the background noise.
(2)The neighborhood average method is adopted to image the target and background noise in the distance the water division, extract the target in the image, the information such as the location of the target is obtained for the further lay the foundation.
In the research literature on the basis of extensively in this paper, the image recognition system was carried out, and with relatively large amounts of text and concrete examples, through the use of the commonly used language and software simulation of obstacle recognition based on digital image processing was studied, and obtained the ideal recognition results.
Key words Image processing Target identification Edge detection Visual navigation
目 录
第一章 绪 论 1
1.1 研究的背景 1
1.2 本文的研究目的和意义 1
第二章 论文的研究背景 3
2.1 机器人视觉导航技术的应用及展望 3
2.2 在工业检测中的应用 4
第三章 图像识别系统 8
3.1 图像预处理 8
3.1.1 灰度化和二值化 9
3.1.2 边缘检测 10
3.2 形态学处理 12
3.3 图像的识别 14
3.4 小结 15
第四章 基于数字图像处理的障碍物识别 16
4.1 仿真环境简介 16
4.2 MATLAB处理 18
4.2.1 灰度化和二值化 18
4.2.2 图像数据处理 20
4.2.3 形态学处理 21
4.2.4 滤波处理 21
4.2.5 图像锐化和目标识别 23
4.3 小结 24
第五章 总结与展望 25
致 谢 26
参考文献 27
附录一（程序代码） 29
附录二（程序运行结果） 31
1.85万字
自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用
摘要 数字图像处理就是利用计算机对图像信息进行加工，以满足人的视觉心理或者应用的需求。图像识别所讨论的问题，是研究用计算机代替人自动地处理大量的物理信息，解决人类所不能识别的问题。对于计算机来说，在实际工作环境里，图像场景已有较大的变化。因此要区分图像属于哪一类，往往要通过一系列关键技术来实现。由此产生的图像识别方法也有很多。
本文以水面障碍物目标（竹竿、渔网等）的图像识别为例，从白天自然光条件下的图像识别方法入手，展开研究。本文以数学图像处理为重点，较详细地论述了对水面上障碍物目标进行图像识别的技术和过程。由于采集到的图像目标和背景灰度色差不是很明显，对于的图像分割不适合采用色差分割法，于是，本文采用了边缘检测的方法进行识别。包括图像预处理、边缘提取、噪声去除、图像锐化和领域平均法处理等的主要过程。最终达到目标识别的目的。研究结论如下：
（1）灰度化处理使原来的彩色图像灰度化，并进行图像缩放以减少计算量，提高运算效率，对灰度图像进行边缘检测，滤波和锐化，突出目标，削弱背景噪声。
（2）采用邻域平均法对图像中的目标和远处水面背景噪声进行分割，提取出图像中的目标，为进一步得到目标的位置等信息打下基础。
本文在较广泛地调研文献的基础上，对图像识别系统进行了较为全面的综述，并以较为大量文字和具体的实例，通过使用常用的仿真语言和软件对基于数字图像处理的障碍物的识别进行了研究，获得了较理想的识别结果。
关键词： 图像处理 水面目标识别 边缘检测 视觉导航
Abstract Digital image processing is the use of computers for image information processing to meet the person's visual psychology or application requirements. Issues discussed at image recognition, is the study of automatically replace people use your computer to work with large amounts of physical information, solve the problem of human beings does not recognize. For the computer, in the actual working environment, image scene has a larger change. Therefore, to distinguish between images fall into which category, often through a series of key technology to achieve. The resulting image recognition also has many kinds of methods.
Based on the target surface obstacles (bamboo, fishing nets, etc.) of image recognition, for example, from the natural light during the day under the condition of image recognition method of study. Focusing on mathematical image processing, this paper discusses on the surface of the water obstacles target image recognition technology and process. Because of the collected image object and background gray color difference is not very obvious, for the image segmentation is not suitable for color segmentation method is used to, so, in this paper, the edge detection method was adopted for identification. Including image preprocessing, edge detection and noise removal and image sharpening and average method, the main process. Ultimately achieve the goal of target recognition. Research conclusions are as follows:
(1)Gray processing make the original color image gray level and image zooming to reduce the amount of calculation, improve the efficiency of operation, and the gray image edge detection, filtering and sharpening, highlight the objectives and weaken the background noise.
(2)The neighborhood average method is adopted to image the target and background noise in the distance the water division, extract the target in the image, the information such as the location of the target is obtained for the further lay the foundation.
In the research literature on the basis of extensively in this paper, the image recognition system was carried out, and with relatively large amounts of text and concrete examples, through the use of the commonly used language and software simulation of obstacle recognition based on digital image processing was studied, and obtained the ideal recognition results.
Key words Image processing Target identification Edge detection Visual navigation
目 录
第一章 绪 论 1
1.1 研究的背景 1
1.2 本文的研究目的和意义 1
第二章 论文的研究背景 3
2.1 机器人视觉导航技术的应用及展望 3
2.2 在工业检测中的应用 4
第三章 图像识别系统 8
3.1 图像预处理 8
3.1.1 灰度化和二值化 9
3.1.2 边缘检测 10
3.2 形态学处理 12
3.3 图像的识别 14
3.4 小结 15
第四章 基于数字图像处理的障碍物识别 16
4.1 仿真环境简介 16
4.2 MATLAB处理 18
4.2.1 灰度化和二值化 18
4.2.2 图像数据处理 20
4.2.3 形态学处理 21
4.2.4 滤波处理 21
4.2.5 图像锐化和目标识别 23
4.3 小结 24
第五章 总结与展望 25
致 谢 26
参考文献 27
附录一（程序代码） 29
附录二（程序运行结果） 31
