Technical Repair Method of Poyang Bodiless Lacquerware Based on Scale-Invariant Feature Transform Algorithm for Healthcare Vision

Abstract

Abstract Aiming at the problems of poor detection accuracy and low efficiency caused by the lack of image contour scale in the traditional detection method of internal cracks in lacquerware, a technical repair method of Poyang bodiless lacquerware based on scale-invariant feature transform algorithm is proposed. Based on the television noise reduction model, the decomposition model of the surface image of bodiless lacquerware is constructed. The extreme value of the energy function is calculated by using the image energy model. According to the calculation results and the Euler Lagrange equation, the decomposed surface image of bodiless lacquerware is obtained. According to the surface image decomposition model of bodiless lacquerware, the structure curvature and color of the defect image of bodiless lacquerware surface are obtained, and the similarity edge is measured to get the similarity edge. Through the similarity edge, the connection of the defect part of the image is completed, and the reconstructed complex surface image of bodiless lacquerware is obtained to complete the technical repair of Poyang bodiless lacquerware. The experimental results show that the research method has higher detection accuracy, faster detection speed, better efficiency, accuracy, and feasibility.