Tyre X-ray Inspection And Multi-textural Image Analysis Technology

Textural defects analysis is one of the main research topics in computer vision inspection field. Image defects can be detected and recognized by analyzing anomaly of texture. However, in complex multi-texture images, for example, in tyre X-ray image, it is difficult to represent characteristics of textures and each texture layer must be segmented and extracted firstly. Now the most common methods of texture analysis are structural analysis method, statistical method, model method and signal processing method, etc. However, it is unable to acquire texture features in complex multi-textural images directly. In this dissertation, a new multi-textural features extraction model and system method has been proposed to analysis tyre X-ray images. In this model, each texture component has been extracted and segmented by spectrum filtering method. Then using textural statistical and structural method, some textural features, such as direction, period, edge, shape, consistency, had been extracted.A new method has been proposed to improve the performance of directional decomposition process in tyre X-ray images. In this method, orthogonal-separable directional filters have been innovatively designed to decompose tyre X-ray images based on thire texture characteristics. Gauss function has been used to modulate the frequency response of filters. So that Gibbs effect has been removed and the capability of anti-spectrum-aliasing has been improved.According to the spectrum characteristics of tyre X-ray images, a multi-channel Gabor filtering method is proposed to substitute Gabor transform to implement joint time-frequency analysis of images. The construction method of filter bank has been researched. So that the extraction complexity of textural features has been decreased and based on these features, the multi-texture segmentation and extraction of tyre X-ray images has been reached.According to the structural characteristics of texture in tyre X-ray images, an effective systematic method has been proposed to inspect X-ray defects. First, first-order statistics has been used to extract texture features and segment the region of texture anomaly. Second, skeleton of texture elements has been extracted by searching of feature points in local region and the vectoriazation of skeleton has been reached by directional searching arithmetic. Based on vectors of texture skeletons, 7 parameters are proposed to describe structure of texture and X-ray texture. At last, according to parameters, tyre X-ray defects have been detected and recognized.According to the analysis of application requirements in tyre Automatic X-ray Inspection System (AXIS), the joint modularization program method of C# and Matlab COM has been used to implement the AXIS. The experimental results showed that tyre X-ray defects had been inspected effectively by AXIS, the accurate rate had reached 99.95% and AXIS function had met the command of automation and intelligence.