Research on non-linear visual matching model under inherent constraints of images

Visual matching of plane images has promoted the development of artificial intelligence and digital vision. High-precision visual matching can promote the innovation of geometric measurement, visual navigation and other fields. Therefore, a non-linear visual matching model with inherent constraints is established in this paper. First, according to the principle of visual imaging, a non-linear conversion model of visual point coordinates is proposed, and the deviation of coordinate points is proofread. Then, inherent boundary constraints are introduced into the model to improve the accuracy of visual matching. Finally, through analysis and evaluation of error, results are generated showing that the visual matching model can effectively solve the shortcoming of low-matching accuracy in feature points, and provide more accurate data support for 3D calculation of images.