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developed, and image splicing has gradually been replaced by networked recognition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