Target object segmentation method and related device

A target object segmentation method, comprising:

• obtaining an input image containing a target object in a video;
• inputting the input image to a preset target object segmentation model, and outputting a first target object segmentation image after a segmentation is performed on the input image by the target object segmentation model, wherein the target object segmentation model is a trained neural network which has learned a target object segmentation function;
• performing a target object contour segmentation on the input image to obtain a second target object segmentation image, wherein the second target object segmentation image is generated according to a difference between the input image and a previous frame in the video;
• performing a merging operation on corresponding pixels in the first target object segmentation image and the second target object segmentation image, to obtain a final target object segmentation image as a binary image, which only contains black and white pixels and represents the target object by using object pixels with a first logic value different from background pixels with a second logic value;
• wherein, if one of a pixel in the first target object segmentation image and a corresponding pixel in the second target object segmentation image, which are subjected to the merging operation, is a target object pixel, that target object pixel is presented as a pixel located at a corresponding position in the final target object segmentation image after the merging operation is performed,
• wherein after the merging operation, the target object segmentation method further performs an image expansion processing on the binary image, wherein the image expansion processing comprises:
• setting a center pixel of a lattice array in the binary image as one of the object pixels when at least one other pixel in that lattice array is determined as a pixel of the target object.