The Measurement Of Test Sieve And Metal Mesh Based On Digital Image Processing

Test sieve is a kind of powder detection tool which is widely used in pharmaceutical industry, microorganism industry and aerospace materials, etc. With the rapidly development of medical technology, biotechnology, and polymer materials, more than half of raw materials and samples are composed of powder, and the test sieve is playing a main role as the measurement of powder detection.The measurement of the interior angles, the mesh size and the size of wire diameter is based on the industrial testing specifications, the rectangular characteristic of the test sieve and the modern image processing methods. This paper deals with the image data processing of the test sieve, the edge extraction of mesh and the improvement of the edge detection approach on the basis of the principle of Wavelet. Comparing with the traditional edge detection algorithms, the improved one is demonstrated to have a higher accuracy. Figuring out the rectangular feature, this paper brought up an idea which could locate the pixels of the edge with higher efficiency and accuracy by improving the traditional Harris corner detection algorithm, avoided the weaknesses of Harris, especially the false detecting rate. Again, to further improve the accuracy of the detection of mesh edge, this paper used a method of Facet sub-pixel algorithm is used to disintegrate the integral pixels being contained in the edge detected by improved Wavelet proposed in the paper, and then the polynomial fitting is used to fit the angles’, the meshes’and wires’edge, it was proved by the experiment and data that the final measurement algorithm can measure all of the three parameters automatically within the margin of industrial specifications.