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Synchronous line-tracking robots based on STM32 总被引:1,自引:0,他引:1
A pair of synchronous line-tracking robots based on STM 32 are designed.Each robot is actually a small intelligent car with seven reflective infrared photoelectric sensors ST 188 installed in the front to track the line.Two rear wheels each driven by a moter are the driving wheels,while each moter is driven by an H-bridge circuit.The running direction is controlled by the turning of a servo fastened to the front wheel and the adjustment of speed difference between the rear wheels.Besides,the light-adaptive line-tracking can be performed.The speeds of the motors are controlled by adjusting pulse-width modulation(PWM)values and an angular displacement transducer is used to detect the relative position of the cars in real time.Thus,the speeds of the cars can be adjusted in time so that the synchronism of the cars can be achieved.Through experiments,the fast and accurate synchronous tracking can be well realized. 相似文献
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针对传统像素级图像融合方法在低频系数融合中,采用偏袒法和平均法容易导致融合图像出现模糊、对比度下降的问题,结合像素级和特征级融合的优势,提出一种基于边缘特征的图像融合算法。算法对于低频系数,采用区域能量自适应加权的方法;对于高频系数,通过对低频边缘特征的融合以指导其融合。分别对红外与可见光图像和多聚焦图像进行实验,并对融合图像进行主客观评价,实验表明,该算法得到的融合图像具有较好的主观视觉效果和客观量化指标,融合性能优于传统的融合方法。 相似文献
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利用小波分解和顶点成分分析的高光谱异常检测 总被引:2,自引:2,他引:0
针对高光谱图像复杂背景影响异常检测结果的问题,提出了一种新的抑制背景的异常检测算法。首先对高光谱图像采用小波分解,将高光谱图像分解成高频图像和低频图像;然后使用顶点成分分析(VCA)方法提取高频图像的端元光谱图;最后使用光谱角匹配(SAM)技术对高光谱图像进行异常检测。实验结果表明,KRX算法相比,本文算法像素目标个数增加32.35%;虚拟个数减少12.12%,计算时间少2个数量级;本文方法的ROC曲线一直位于KRX、PCA-KPX算法的异常检测方法之上,有利于高光谱图像的实时异常检测应用。 相似文献
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