This includes:

• Define Objectives and Requirements.
  The first step is to define the goals and objectives of the vision system. It is key to understand the specific tasks the system needs to perform, such as object recognition, defect detection or tracking.
  Based on this the requirements for the vision system are defined, including image resolution, processing speed and environmental conditions.
• Selection of Hardware Components.
  This may include cameras, lenses, lighting systems, trigger boxes, mounts, cables.
• Choose Software and Algorithms.
  To achieve the task this might either mean to use pre-existing libraries (e.g., Halcon, CVB, Sherlock Dalsa) and/or the development of custom algorithms based on the specific needs of the application.
  It is important to define factors like accuracy, speed, and the complexity of the algorithm at this step in relation to the available hardware.
• Hardware and Software setup.
  Set up of the image acquisition, configuration of the computer and hardware components.
  Calibration of sensors/image system if required (this depends on the application, this is required for 3D applications and calibration of the sensor).
  Set up capture parameters such as exposure time, frame rate, and resolution.
• Development of the Application.
  This includes the development of pre-processing techniques (such as noise reduction or colour correction), feature extraction (such as object recognition, orientation of object), algorithm implementation (to solve the specific task), and to optimise the algorithms for efficiency, taking into account the processing speed and resources available on the target hardware.
• Integration with Other System.
  Integration of the vision systems with other components such as robotic systems, databases, or other control systems.
  Ensuring seamless communication and data exchange between the vision system and other parts of the industrial process.
• Testing and Validation.
  Conducting thorough testing to ensure the vision systems performs as expected and validation of accuracy and reliability of the system.
  SAT/FAT can be provided.
• Optimization and Fine-Tuning.
  Fine-tuning of the system based on testing and validation results. Optimize parameters, algorithms, and hardware configurations to achieve the desired performance.
  Considering feedback from users/operators to make necessary adjustments and improvements.
• Documentation.
  Documentation of the design, implementation, and configuration of the vision system. This may include details on hardware components software algorithms, calibration procedures, and any troubleshooting guidelines.
• Support, Maintenance, and Upgrades.
  Establishing a plan for ongoing support, maintenance, and potential upgrades to the vision system. This may include regular calibration, monitoring the system performance, and updating software or hardware components as needed.