Deep-Learning-Based Surface Texture Feature Simulation for Surface Defect Inspection

Genetic Learning Based Texture Surface Inspection

This paper presents a novel approach of visual inspection for texture surface defects. It is based on the measure of texture energy acquired by a kind if high performance 2D detection mask, which is learned by genetic algorithms. Experimental results of texture defect inspection on textile images are presented to illustrate the merit and feasibility of the proposed method.

Real-time surface inspection by texture

In this paper a real-time surface inspection method based on texture features is introduced. The proposed approach is based on the Local Binary Pattern (LBP) texture operator and the Self-Organizing Map (SOM). A very fast software implementation of the LBP operator is presented. The SOM is used as a powerful classifier and visualizer. The efficiency of the method is empirically evaluated in two...

Exemplar-Based Surface Texture

Realistic rendering of computer modeled three dimensional surfaces typically involves estimation of the reflectance properties of the material to be used for rendering the surface, or use of photographs of the material for texturing instead. Bidirectional texture functions (BTFs) can be used for this purpose, however, full coverage of all viewing and lighting directions desired must be acquired...

Gipsy: Knowledge Based Surface Inspection

Despite of a great demand of automatic image analysis systems in the production industry, the spread of installed systems is still limited. Reasons for this are, among others, the high requirements of image analysis systems with respect to computational effort and accuracy, the high engineering effort for the development of image analysis applications, and thus high investment costs for image a...

Free-Form Surface Matching for Surface Inspection