Image automatic detection system and method thereof

Abstract

The present disclosure provides an image automatic detection system, including a camera and a processor. The camera is configured to capture multiple normal images, multiple abnormal images and images to be detected. The processor includes an input module, an image editing module, a training module and a detection module. The image editing module is configured to center and adjust the angles of the normal images and the abnormal images to be consistent to reduce image noise. The training module is configured to train the adjusted normal images and the adjusted abnormal images with an abnormality detection algorithm to obtain an image automatic detection model. The detection module is configured to analyze the image to be detected using an image automatic detection model to identify whether the image to be detected is normal or abnormal, achieving blur detection and high recognition rate.

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