摘要：Specified craft production is a major characteristic of all complex civilizations, and archaeologists have frequently utilized craft specialization as a distinguishing element in identifying and researching the evolution of political complexity. This study aims to better realize the design of modern craft products, using a combination of digital image processing technique and visual sensing system. The impact of digital technology combined with a visual sensing system on product design is investigated and an improved oriented fast and rotated brief (ORB) feature matching algorithm is designed for target image feature extraction. To verify the performance of the algorithm, different experiments are designed for the accomplishment of purification effect, scale invariance, rotation invariance, and computation time. Results show that the corresponding performance accuracies after continuous purification using the angle constraint method are 99.6%, 99.3%, and 99.7%, respectively, which are significantly higher than the accuracy of a single action. In addition, the absolute value of the error of the rotation angle measured by the improved ORB feature matching algorithm is 0.14° on average. It shows that the improved ORB feature matching algorithm has high matching accuracy. The proposed algorithm improves the accuracy of target image feature extraction and has important significance in image recognition.
