In this paper a novel approach for multiple maneuvering targets tracking in infrared image sequence is proposed. For each
target, the measurement weights and model weights, which are essential for data association and multi-model based
filtering, are determined jointly by quadratic programming. The proposed method avoids events enumeration process in
traditional tracking algorithm such as JPDA and hill-climbing optimization process in classical EM-based algorithm.
Simulation results show that compared with IMM+JPDA and recursive EM based algorithm, the proposed quadratic
programming based algorithm can achieve good performance in both tracking accuracy and computational complexity.
In this paper an adaptive inverse filter is employed which suppress noise within the bandwidth of the desired signal with the particular aim to improve the accuracy of WIM systems. Within the framework of the FIR filter, the inverse system of WIM system is constructed by using LMS adaptive algorithm as an innovative filter. Moreover, an additional filter, a noise filter, is adopted as well, in order to best improvement the measurement accuracy. The final results processed by cascaded filter combination show a significant improvement in estimation of static weight of moving vehicles.
Heat sources recognition is very important for Printed Circuit Board (PCB) infrared thermal imaging diagnosis and several recognition techniques have been proposed by former researchers. In this paper the heat sources detection based on wavelet transforms is investigated. Cubic B-spline function is chosen as the smoothing function and its first derivative as the wavelet function. Fast recursive decomposition algorithm for 2-dimensional signal is used to compute wavelet transforms at different scales. Then the temperature gradient distributions on the thermal image of PCB under test can be determined and the bound of the heat sources can be located on the base of the gradient information. Multi-scale edge detection technique offered an opportunity to recognize the heat sources at the same time distinguishing them from the noises by choosing proper detection scale. Experimental results suggest that heat source in PCB thermal image can be recognized successfully using the proposed method.
In the diagnosis of Printed Circuit Board (PCB) based on infrared radiation, emissivity correction must be performed on the thermal image to retrieve the true temperature distribution on the PCB surface. Taking the measured PCB surface temperature as a combination of its true temperature distribution and its emissivity distribution, a non-linear filtering method was proposed to separate the true temperature from this combination based on the differences in the continuity of these two contributions. As the key step of the proposed method, the discontinuity detection is implemented through wavelet transform. Experimental results indicated that the true temperature distribution can be estimated precisely by the proposed method.