摘要： The edge preserving image segmentation required by online shopping malls or the design ?eld is clearly limited to pixel based image machine learning, making it dif?cult for the industry to accept the results of the latest machine learning techniques. Existing studies of image segmentation have shown that using any size square as a study unit without targeting meaningful pixels provides a simple method of learning, but produces a high error rate in image segmentation and also there is no way to calibrate the resulting images. Therefore, this paper proposes image segmentation techniques through superpixel based machine learning to develop technologies for automatically identifying and separating objects from images. In addition, the main reasons for superpixel based imagecut using object detection is to reduce the amount of data processed, thereby effectively delivering higher computational rates and larger image processing.