Trace Image Detection Technology Based on Deep Learning

The application of digital image processing based on depth learning in trace detection technology is a technology that allows users to analyze various types of images and data. It can be used to detect defects in materials, detect contamination, identify defects or anomalies, and inspect components. This software has been widely used by manufacturers and inspectors because it has many advantages over traditional methods. The main benefit users get from this software is that they can provide high-quality results in a short time. In addition, it can help reduce costs while increasing productivity. This paper mainly studies digital trace detection. Firstly, the digitization of the trace inspection acquisition process is introduced, and the technical change process in the trace acquisition process is introduced from two aspects of image acquisition and text acquisition; Then the specific process of trace inspection is divided into two parts: pretreatment and inspection. This paper introduces the process of image geometric processing, image arithmetic processing, image enhancement, image restoration and image compression coding in the early stage of trace detection, provides the detection basis for the subsequent trace detection process, and summarizes the application of digital technology in trace detection; Finally, it describes the digitalization process of the establishment and management of trace archives.