| Summary: | 碩士 === 國立虎尾科技大學 === 機械與電腦輔助工程系碩士班 === 101 === This study investigates the characteristics of spectral illumination and object recognition for image vision. In general, the image inspections for object recognition usually depend on different spectral illumination and geometric features. Therefore, the angle, intensity, transmittance and spectral analyses of light sources are analyzed for image inspections. The objects for image inspections have the fasteners (gasket and thread), coins and bicycle accessories. The feature inspections of the object contain the geometry size, roundness, texture feature and image stitching that are recognized using the image morphology.
Results showed that the defect inspections of the gaskets based on XOR image subtraction are successfully recognized. The inspection errors of the outside and inside diameters for the gaskets are ±1% and ±2.5%, respectively. The frequency domain transformation of Fourier spectrum is used to identify the texture of the screw thread. Moreover, the spectrum response of Sr(θ) and Sθ(r) can recognize the destructive screw thread. The pitch error of the M10×1.5 and M8×1.25 is ±0.01mm and the error of the M6×1.0 and M4×0.7 is ±0.03mm.For the recognition of the coins, we use a circle crop to separate the image of coin and the background. Then, the head or tail of the coins is determined using the Sobel detection and image subtraction algorithm. Finally, the new or old coin is recognized using the average contrast and the smoothness. Additionally, the bicycle accessories with narrow type are investigated using scale-invariant feature transform (SIFT) algorithm. The dimensional error of the bicycle accessories is ±1% for the length and the width.
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