| dc.description.abstract | In our research, a series of slab images matching’s program model was designed by the software of Borland C ++ builder. We also try to implement the slab simulate test for the related information of the slab image. It contains the noise, seam position, crack area, and destruct situation of the slab, etc. There are four steps in the process of the slab image matching. The four setups are the automatic catching pavement images, image normalization, the slab image preprocessing, and the image matching, respectively.
The image matching which is discussed on the same position of the slab image simulates the obvious noise and the variation of the slab image by crack situation. In our research, a suitable image preprocess is needed before the proceeding of the slab image matching. An optimum binary image is very important for image preprocessing. Among the optimum binary image through four kinds of edge detections, the method of canny edge detection has better effect for fine features. Therefore, the inner information of the slab image which has better effect can be found by the image histogram. In this image histogram, the possible crack or the destructive area inside the image can be observed by some growth situations of pixels accumulating quantity, especially. The destructive degree, destructive positions, and the destructive rate of the block inside the slab image can also be observed by difference of the average gray value on the block images.
This research which utilizes preliminary development of the rigidity pavement slab image matching systems can carry out recognizing the broken slab images by extracting the complete broken slab image. It will be an efficient and complete automatic estimative pavement broken images systems in the future. | en_US |