Automatic detection of micro image edges for micro accessories

As Micro Processing Technology Matching based Micro Image Edge Detection method (MPTM-MIED) developed by previous research can not automatically detect the micro image edges of micro accessories in real time, this paper designs the MPTM-MIED based on BP neural network again. Then, it proposes a novel Automated Micro Image Edge Detection method (AMIED) to extract edges of micro images automatically. To verify the feasibility of the proposed method, the edges of micro images from micro accessories fabricated by four different methods are extracted by AMIED and the sizes of micro accessories by line cutting are measured. Obtained results show that the detected edges by AMIED and MPTM-MIED are almost the same, and the AMIED has better edge-connectivity as compared with some common detection algorithms. Furthermore, the analysis results indicate that the measured sizes by AMIED are almost equal to those measured by MPTM-MIED and they are more close to those measured by the universal tool measuring microscope as compared with that of the Canny algorithm. Because the method has no more need of selecting edge transition region, it improves the detection speed and can measure the sizes of micro accessories in real time.