Fig. 1. Typical periodic texture image and spectrum characteristic. (a) Fabric image; (b) 3D spectrum with a series of characteristic peaks

Fig. 2. Simulation texture image and spectrum characteristic. (a) Simulation texture image; (b) 3D spectrum; (c) transverse spectrum and characteristic peaks

Fig. 3. Simulation results of texture image with uniformity error and spectrum characteristic. (a) Simulation texture image; (b) 3D spectrum; (c) transverse spectrum characteristic peaks and peak diffusion

Fig. 4. Correlativity between inspected uniformity error and preseted uniformity error

Fig. 5. Analysis of the relationship between the texture inclination α and the rotation angle of spectrum characteristic point β. (a) Decomposition diagram of d; (b) spectrum characteristic analysis

Fig. 6. User interface in the static density test software. (a) Texture image to be detected; (b) 2D spectrum and feature marker; (c) rotation-corrected image; (d) feature marker in the corrected image; (e) control of execution and output texture detection results

Fig. 7. Histogram analysis of error of measurement results. (a)Data measured by proposed method; (b) data measured by the method in Ref. [20]

Fig. 8. Real-time acquisition and inspection system. (a) Structure of acquisition system; (b) display interface of inspection result

Fig. 9. Fabric uniformity inspection results. (a)~(d) Fabric of uniform texture; (e)~(h) fabric stretched along transverse direction

Fig. 10. Paper counts based on spectrum characteristics. (a) Cross-section image of paper; (b) preprocessing image; (c) 3D spectrum; (d) spectrum characteristics

Fig. 11. Wood texture inspection based on spectrum characteristics. (a) Wood texture image; (b) preprocessing image; (c) 3D spectrum; (d) spectrum characteristics

Fig. 12. Inspection of microstructural arrays based on spectrum characteristics. (a)Texture image of microstructural arrays; (b) preprocessing image; (c) 3D spectrum; (d) spectrum characteristics