【免费】基于python+OpenCV的全景图像拼接系统源码数据库论文.docx资源-CSDN文库

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摘要

进入二十一世纪之后，网络发展越来越迅速，人们的很多生活与消费习惯都随之

发生了改变。在图像识别或拼接技术不发达的年代，人们是无法通过电脑进行两个图

片之间的拼接的，人们通常是使用一些简单的图片处理技术或者通过人工进行拼接，。

但这种形式费事费力，因为往往一张图片是有很多元素组成的，负责此项工作的工作

人员的数量肯定是有限的，所以如果想完成高质量的图片拼接需要很长的周期，并且

对工作人员来说强度和难度也非常的大。不过随着许多传统的行业逐渐与互联网接轨，

各种图像处理及拼接技术越来越发达，图像的拼接也逐渐被网络化的识别系统所替代

了。在计算机刚开始发展的时候就出现了许多的图像拼接或图像识别系统，但是因为

技术的限制导致系统并不完美，有很多不符合使用者使用习惯的瑕疵，也有很多的功

能缺陷。随着计算机编程语言的不断发展和移动设备的出现，图像拼接服务逐渐朝着

更专业、更精准、更效率的方向发展。

本系统前台界面使用了最新的 HTML5 技术，使用 DIV+CSS 进行布局，使整个前台

页面变得更美观，极大的提高了用户的体验，另外本系统无论是使用电脑的浏览器进

行访问还是使用移动设备进行访问，都可以保证网站正确的排版。后端的代码技术选

择的是 PYTHON，PYTHON 语言是当下最常用的编程语言之一，可以保证系统的稳定性

和流畅性，PYTHON 可以灵活的与数据库进行连接。本系统的数据使用的 MYSQL 数据

库，它可以提高查询的速度，增强系统数据存储的稳定性和安全性。而本系统的图像

拼接技术以 OpenCV 为核心，最大化提升图片拼接的质量。

关键词：图像拼接；OpenCV；PYTHON；MySQL

Abstract

After entering the 21st century, the network has developed more and more

rapidly, and many people's life and consumption habits have changed accordingly. In

the era when image recognition or stitching technology is not developed, people can't

splice between two images by computer. People usually use some simple image

processing technology or manually splice,. However, this form is time-consuming and

laborious, because often a picture is composed of many elements, and the number of

staff responsible for this work must be limited. Therefore, it takes a long period to

complete high-quality picture splicing, and it is also very difficult and intense for staff.

However, with the gradual integration of many traditional industries with the Internet,

various image processing and splicing technologies have become more and more

developed, and image splicing has gradually been replaced by networked recognition

systems. At the beginning of the development of computer, many image mosaic or

image recognition systems appeared. However, due to technical limitations, the

system is not perfect. There are many defects that do not conform to the user's usage

habits, as well as many functional defects. With the continuous development of

computer programming languages and the emergence of mobile devices, image

mosaic services are gradually moving towards a more professional, accurate and

efficient direction.

The system's foreground interface uses the latest HTML5 technology and uses

DIV+CSS for layout, which makes the whole foreground page more beautiful and

greatly improves the user's experience. In addition, the system can ensure the correct

layout of the website whether it is accessed using a computer browser or using a

mobile device. The back-end code technology is PYTHON. PYTHON language is one of

the most commonly used programming languages at present, which can ensure the

stability and smoothness of the system. PYTHON can flexibly connect with the

database. The data of this system uses the MYSQL database, which can improve the

query speed and enhance the stability and security of the system data storage. The

image mosaic technology of this system takes OpenCV as the core to maximize the

quality of image mosaic.

Key words: Deep learning; System; PYTHON； MySQL

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