We propose a practical method for the design of a light-emitting diode (LED) rear fog lamp based on freeform micro-surface reflectors. The lamp consists of nine LEDs and each of them has a freeform micro-surface reflector correspondingly. The micro-surface reflector design includes three steps. An initial freeform reflector is first built based on the light energy maps. The micro-surface reflector is then constructed on the bias of the initial one. Finally, a two-step method is designed to optimize the micro-surface reflector. With the proposed method, a module is designed and LCW DURIS E5 LED source whose emitting surface is 5.7 mm × 3.0 mm is adopted for simulation. A prototype is also assembled and fabricated to verify the real performance. Both the simulation and experimental results demonstrate that the luminous intensity distribution can well fulfill the requirements of ECE No.38 regulation. Furthermore, more than 79% energy can be saved when compared with the rear fog lamps using conventional sources.
Affected by the point spread function of optical microscopic imaging system, the edge of microscopic structure and target becomes smooth, at the same time the edge pixel contour distortion is serious because of noise. These factors make positioning precision reduced by using the traditional edge detection algorithm. Thus combining direction information measure and moment invariant theory, the paper puts forward edge detection algorithm of sum and difference of axial neighborhood, and then formulates the high order sum and difference of axial neighborhood to localize sub-pixel edge by using high-order spatial gray moment. Through artificial simulated image the algorithm is test, results show it has stronger antinomies' ability and high positioning accuracy. The algorithm is used in measurement experiment for line width of 1.272μm, the uncertainty is only 0.067μm. This shows that the algorithm reached high accuracy for measurement.
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