CAJ | 학술논문

为了精确定位人体目标区域, 以达到照明节能最优化, 提出了一种改进的Canny算子与数学形态学相结合的图像处理技术, 对室内图像进行边缘检测和噪声处理, 得到含有人体目标的二值化图像, 将得到的二值化人体背影模板的七个Hu不变矩作为LVQ神经网络的输入向量, 训练出能够准确识别出人体背影的网络; 再建立出室内图像特征与人体数量和坐标的匹配模型, 从而根据人体坐标和数量来实现对灯具的优化控制。仿真和实验结果表明, 改进的Canny算子与LVQ神经网络的结合对室内光环境的优化控制具有很好的应用价值。
위료정학정위인체목표구역, 이체도조명절능최우화, 제출료일충개진적Canny산자여수학형태학상결합적도상처리기술, 대실내도상진행변연검측화조성처리, 득도함유인체목표적이치화도상, 장득도적이치화인체배영모판적칠개Hu불변구작위LVQ신경망락적수입향량, 훈련출능구준학식별출인체배영적망락; 재건립출실내도상특정여인체수량화좌표적필배모형, 종이근거인체좌표화수량래실현대등구적우화공제。방진화실험결과표명, 개진적Canny산자여LVQ신경망락적결합대실내광배경적우화공제구유흔호적응용개치。
In order to positioning the target area of human body to achieve the optimization of the lighting energy saving, this paper put forward an image processing technique combined the improved Canny operator and mathematical morphology, detected the edge of the indoor image and noise processing, and then to get the binary image containing human as target. It took seven Hu moment invariants of binary human figure template as the input vector of LVQ neural network, which were calculated to get, and trained network to identify the human figure accurately. After that, building the matching model of indoor image characteristics and the personnel quantity and coordinates was well designed to realize the optimization control to indoor lamps according to personnel quantity and coordinates. Simulation and experimental results show that with the combination of the improved Canny operator and LVQ neural network has quite application value on the optimization control of indoor light environment.