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How to solve the frame loss problem of industrial cameras in "Machine Vision System"

2026-08-24

Dernières nouvelles de l'entreprise How to solve the frame loss problem of industrial cameras in
Three main reasons why industrial cameras drop frames:
1. Industrial vision software application part

Vision software has a buffering mechanism for waiting for image space calculations. In order to increase the image buffering time, the program operations can be processed. However, if the computer CPU processing speed is slower than the image speed, it will cause the cache space to be overloaded and frame loss problems will occur.

Industrial camera drops frames

2. Hardware design of the industrial camera itself

Industrial cameras convert images from optical signals into ordered electrical signals. The image sensor transmits the image to the USB chip on the camera, and the USB transmits the image to the computer. If the computer terminal system is busy at a certain moment, the image cannot be received in time, and subsequent images are transmitted, resulting in the loss of the unreceived part of the image. Industrial cameras require memory buffer space, otherwise frame drops will occur.

3. Hardware PC system part

The PC part mainly relies on hardware drivers. The most important thing is the power of the driver and how many threads in the system have core mode to divide the CPU time. The received power is not good, and the industrial camera does not have a good buffer memory, which often causes frame loss.

Industrial camera drops frames

In machine vision systems, the frame rate of industrial cameras is often very large, and the cache of industrial cameras is also limited. This is mainly an auxiliary function for temporary busy processing of the scheduling system. The speed of machine vision software is slower than the speed of industrial camera images. After a long period of time, it will cause the loss of software buffer saturation and overflow. Therefore, frame loss will occur in both USB interfaces and GigE interfaces. Therefore, it is very important to optimize the processing speed of machine vision software.