What is the difference between threshold segmentation and edge detection in image segmentation?

1, threshold segmentation is a method to highlight the part of the image we are interested in. After binarization (or multivaluing), the target object will be given a specific gray value, mainly focusing on the gray characteristics of the object, which is represented by threshold segmentation. Edge detection is a method to find out the edge of an object, mainly through the algorithm to detect the gray features of the edge.

2. The focus of binary threshold segmentation is to find the binary threshold, and then use the threshold to separate the target from the background. The focus of most edge detection is to determine the difference operator and make gray difference in the neighborhood.

3. The general process is to get the differential gray image by edge detection, and then divide it into two values by threshold.

The two concepts we usually talk about are vague and belong to an intersection. The gray level of the edge is prominent, and it can be directly binarized without algorithm processing, so threshold segmentation can be regarded as an edge detection method. If the edge is not prominent, difference operator or other methods should be used to highlight it first, then threshold segmentation is only a means to reflect the edge.