In visual detection, threshold is an important concept that is used to determine whether the brightness value or color value of a pixel in an image meets a certain condition. Threshold can help to segment an image into different regions or objects, and is one of the commonly used techniques in image processing and analysis.

The most common application is binarization of images, which divides the pixel values in the image into two categories: pixels that meet the threshold condition are set to one value (usually white), and pixels that do not meet the condition are set to another value (usually black).

In addition to simple binarization, multiple thresholds can be used to divide an image into multiple different regions, each with different properties or meanings.

For images with uneven brightness in different regions, adaptive threshold method can be used to dynamically adjust the threshold value according to the local information around the pixel.

By setting the threshold reasonably, we can effectively deal with the noise, edge, object detection and other problems in the image, which has an important impact on the performance and accuracy of the vision detection system.