Electrochemiluminescence (ECL) behavior of luminol on an indium tin oxide (ITO) electrode modified with platinum nanoparticles (PtNPs) was investigated in a neutral aqueous solution using the conventional cyclic voltammetry (CV) technique. Experimental results indicated that the ECL behaviors of luminol on the PtNPs modified electrode showed significant difference from those on the bare ITO or bulk platinum electrodes. Five ECL peaks were found at 0.60, 0.92, 0.70, -0.44 and -1.16 V versus a saturated calomel electrode (SCE), respectively. The ECL peaks were found to depend on the reaction medium conditions including the type of electrolyte, pH value, the presence or absence of O2 and the different kinds of nanoparticles, as well as the scan direction and range of the applied potential. Furthermore, ECL peaks at -0.44 and -1.16 V could only be obtained on the PtNPs/ITO electrode. The surface state of the electrode was characterized by ultraviolet-visible (UV-Vis) absorption, scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). A mechanism for luminol ECL on the PtNPs/ITO electrode was proposed. The excellent ECL properties of luminol on the PtNPs/ITO electrode in the neutral medium revealed a great potential for analytical applications to biological samples.
In video surveillance, there are many interference factors such as target changes, complex scenes, and target deformation in the moving object tracking. In order to resolve this issue, based on the comparative analysis of several common moving object detection methods, a moving object detection and recognition algorithm combined frame difference with background subtraction is presented in this paper. In the algorithm, we first calculate the average of the values of the gray of the continuous multi-frame image in the dynamic image, and then get background image obtained by the statistical average of the continuous image sequence, that is, the continuous interception of the N-frame images are summed, and find the average. In this case, weight of object information has been increasing, and also restrains the static background. Eventually the motion detection image contains both the target contour and more target information of the target contour point from the background image, so as to achieve separating the moving target from the image. The simulation results show the effectiveness of the proposed algorithm.
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