Development Of Cross-Platform Software And Research On Algorithm For The WLAN Camera

Due to the update of computer science and network technology,combining network and other technologies to create new applications brings new power to future technological development.WLAN camera based on wireless transmission has been widely used in various industries,and camera software is an important part,whose quality affects the performance of the entire system.In this paper,a multifunctional WLAN camera software covering Windows/macOS/Linux desktop platform and iOS/Android mobile platforms is developed.The software can not only ensure the stable and high-fidelity output of image data,but also integrate the subsequent analysis and processing functions of video and images,and provide a friendly graphical user interface.The communication between cameras and clients mainly depends on a self-designed network communication protocol.Based on TCP/IP,protocols including camera video streaming protocol,camera discovery/network configuration protocol and camera parameter transfer protocol are designed and message is encapsulation to ensure real-time and stable data transmission.According to the function,the software is divided into the following modules:basic function module,parameter adjustment module,measurement module and image processing and application module.In this paper,the overall framework of the software is designed according to the functional characteristics of the module.Firstly,the module abstraction is completed,and the platform independence of their functions is realized at the source code level.Secondly,the software GUI is designed according to different platform characteristics.In this paper,we study and integrate the auto-focus algorithm and depth-of-field expansion algorithm into the image processing and application module of the softwareIn the auto-focus module,the software receives the focus area information selected by the user and sends it to the WLAN camera to control the stepper motor movement.Each step of the motor updates the focus evaluation function value of the focus area,and then uses the hill-climbing search method as the focus strategy.Tests are performed through multiple experiments,and the results show that this method can accurately and quickly achieve autofocus,and can be adapted to both stereo and biological microscopy imaging systems.The depth-of-field expansion algorithm takes the microscopic image video stream transmitted by the WLAN camera as the data input.After image preprocessing of image filtering and image registration,the image fusion based on the Laplacian pyramid method is used to finally obtain an image containing enough detailed and large depth of field image.By evaluating and analyzing the results of multiple groups of experiments,it is shown that the algorithm can retain image details well and has better robustness.Finally,a test platform was built to test the software,which was successfully applied to WCAM series and X(F)CAM series cameras,and successfully completed the research objectives.