Proc. SPIE. 6027, ICO20: Optical Information Processing
KEYWORDS: Target detection, Digital signal processing, Detection and tracking algorithms, Image processing, Field programmable gate arrays, Image analysis, Data processing, Signal processing, Target recognition, Data communications
Template matching is the process of searching the present and the location of a reference image or an object in a scene image. Template matching is a classical problem in a scene analysis: given a reference image of an object, decide whether that object exists in a scene image under analysis, and find its location if it does. The template matching process involves cross-correlating the template with the scene image and computing a measure of similarity between
them to determine the displacement. The conventional matching method used the spatial cross-correlation process which is computationally expensive. Some algorithms are proposed for this speed problem, such as pyramid algorithm, but it still can't reach the real-time for bigger model image. Moreover, the cross-correlation algorithm can't be effective when the object in the image is rotated. Therefore, the conventional algorithms can't be used for practical purpose. In
this paper, an algorithm for a rotation invariant template matching method based on different value circular projection target tracking algorithm is proposed. This algorithm projects the model image as circular and gets the radius and the sum of the same radius pixel value. The sum of the same radius pixel value is invariable for the same image and the any rotated angle image. Therefore, this algorithm has the rotation invariant property. In order to improve the matching speed and get the illumination invariance, the different value method is combined with circular projection algorithm. This method computes the different value between model image radius pixel sum and the scene image radius pixel sum so that it gets the matching result. The pyramid algorithm also is been applied in order to improve the matching speed. The high speed hardware system also is been design in order to meet the real time requirement of target tracking system. The results show that this system has the good rotate invariance and real-time property.
In many computer vision tasks, in order to improve the accuracy and robustness to the noise, wavelet analysis is preferred for the natural multi-resolution property. However, the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour, the Zernike moments are introduced, and a novel Starting-Point-Independent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours, and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments, consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image, which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient, precise, and robust.
Proc. SPIE. 5623, Passive Components and Fiber-based Devices
KEYWORDS: Target detection, Digital signal processing, Digital image processing, Detection and tracking algorithms, Image processing, Field programmable gate arrays, Image analysis, Signal processing, Target recognition, Evolutionary algorithms
In order to resolve the contradiction between real-time and arithmetic complex in television tracking capture system, the paper discusses a real-time target track processing system which is constructed by high performance DSP chipset TMS320C6416 as core digital processor, huge reprogrammable logic chipset CPLD as system logic controller and field reprogrammable array FPGA as image preprocessing chipset to sampled video digital image. In the same time, the author also improved target capture arithmetic by introducing a kind of fast image correlation matching arithmetic based on evolutionary algorithms. Major parts put on hardware construct, working theory and new image correlation matching algorithms. Furthermore the comparison of the performance provided by this method with conventional matching algorithms is discussed. Theoretical analysis and simulation results show that the proposed algorithm is very effective.