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<p class="9"><span>Machine vision means to carry out measurement or judgment with machine instead of human eyes. In the field of target recognition, optical correlation technology is a main way to realize machine vision. Targets can be recognized and located with high precision</span><span> </span><span>taking advantage of optoelectronic hybrid joint </span><span>transform</span><span> correlator (OHJTC). However, when scale or angular distortion of the detected target exists relative to the reference template, the intensity of correlation peaks will decrease to a great extent, which restricted the recognition results greatly. In this paper, the development and principle of maximum average correlation height (MACH)</span><span> </span><span>algorithm is introduced. Through amounts of experiments, t</span><span>he control</span><span>ling</span><span> parameters</span><span> </span><span>of the synthesized filter</span><span> are optimized</span><span>, which makes MACH filter suppress background noise and widen recognition range of targets</span><span>. To show the feasibility of this algorithm, simulative and optical experiments of the improved MACH filter are carried out. As an example, the recognition results of a fighter target in sky</span><span> </span><span>are given, which shows </span><span>the </span><span>scale</span><span> </span><span>distortion tolerance can reach up </span><span>to </span><span>±</span><span>23%</span><span>. The actual effect of the improved MACH filter algorithm has been confirmed very well</span><span>.</span><span> <o:p></o:p></span></p>
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FINGER KNUCKLE PRINT BASED VERIFICATION USING MINIMUM AVERAGE CORRELATION ENERGY FILTER