Optimized image recognition based sewing pattern file auto-generating method for intelligent industrial equipments

The development of embedded system (ES) promotes the trend that the numerical-control equipment becomes more networked and intelligent. ES is the kernal of network and intelligence, yet the image data with contained information is the key point to realize high antomatization and intelligence of ES. The overall automatization level of industrial equipment becomes higher than before. However, in some basic industries, such as the sewing industry, the automatization is backward. This paper analyzes the working mechanism of current pattern-designing software and concludes that the system input is complicated, and the usability and automatization is low. To deal with the problem, the paper proposes a sewing pattern generating method based on optimized image recognition. This method is data-driven, which includes image calibration, edge detecting and curve fitting to simplify the system input. A new algorithm is designed to transfer the system input from vectors to scalars, or to accept both of them, which improves the system's scalability and usability. Corresponding software is developed and the results show that it is more reliable, and it can satisfy the industrial requirements in an acceptable degree.