Correlation Techniques in Adaptive Template Matching With Uncalibrated Cameras (original) (raw)
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Correlation techniques in adaptive template matching with uncalibrated cameras
Vision Geometry III, 1995
The use of correlation as a measure of similarity between two signals is a well known technique. Correlation is commonly used in stereo vision to solve the correspondence problem. In this context the aim is to nd the position of a point in one of the two images of a weakly calibrated stereo pair which corresponds to a point in the other image. Template windows are chosen from the rst image as 2D information samples to be matched in a region of interest of the second image. We propose a technique which exploits an adaptive template matching. It works as an iterative optimization of the involved parameters with a consequent iterative re nement of the correspondence. Matching is performed by transforming a template window using the current image-to-image a ne transformation and exploiting the epipolar geometry to reduce the degrees of freedom of the template position in the region of interest. As a validation test of the presented technique we report a study on the accuracy of the obtained results with various template sizes. We show that subpixel accuracy can be reached with relatively small templates. A major concern of our work is the accuracy of the correspondence. Higher accuracy of the correspondences results in fact in a more realistic reconstruction of the viewed scene. In the case of a stereo pair undergone an estimated distortion of 0.5 pixel (10 m of pixel size) it is shown an accuracy in the correspondence of 3 m for template windows of 17X17 size selected in textured image patches. Experiments are under process to improve the mentioned results.
Computation Elimination Algorithms for Correlation Based Fast Template Matching
Template matching is frequently used in Digital Image Processing, Machine Vision, Remote Sensing and Pattern Recognition, and a large number of template matching algorithms have been proposed in literature. The performance of these algorithms may be evaluated from the perspective of accuracy as well as computational complexity. Algorithm designers face a tradeoff between these two desirable characteristics; often, fast algorithms lack robustness and robust algorithms are computationally expensive. ance of the residue signal will always be less than the existing motion compensation schemes (Mahmood et al., 2007). This result may potentially be used to increase compression of video signal as compared to the current techniques. The fast correlation strategies, proposed in this thesis, may be coupled with this result to develop correlation-based video encoders, having low computational cost.
Modifications in Normalized Cross Correlation Expression for Template Matching Applications
cerc.wvu.edu
This paper analyzes the performance of sum of squared differences (SSD), sum of absolute differences (SAD), normalized cross correlation (NCC), zero mean normalized cross correlation (ZNCC) and several other proposed modified expressions of NCC. Experimental results on real images demonstrate that some of the proposed modified expressions of NCC are more efficient than conventional NCC for template matching. Three of the modified expressions of NCC perform similar to ZNCC however they are computationally less intensive. Modified expressions of NCC were also studied under different values of additive white Gaussian noise. Some of them perform better than ZNCC in terms of successfully found points and computation time for noisy images.
Adaptive least squares correlation — a powerful image matching technique
1985
The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its application to image matching is outlined. It allows for simultaneous radiometric corrections and local geometrical image shaping, whereby the system parameters are automatically assessed, corrected, and thus optimized during the least squares iterations. The various tools of least squares
Equivalence of digital image correlation criteria for pattern matching
Applied Optics, 2010
In digital image correlation (DIC), to obtain the displacements of each point of interest, a correlation criterion must be predefined to evaluate the similarity between the reference subset and the target subset. The correlation criterion is of fundamental importance in DIC, and various correlation criteria have been designed and used in literature. However, little research has been carried out to investigate their relations. In this paper, we first provide a comprehensive overview of various correlation criteria used in DIC. Then we focus on three robust and most widely used correlation criteria, i.e., a zero-mean normalized cross-correlation (ZNCC) criterion, a zero-mean normalized sum of squared difference (ZNSSD) criterion, and a parametric sum of squared difference (PSSD ab ) criterion with two additional unknown parameters, since they are insensitive to the scale and offset changes of the target subset intensity and have been highly recommended for practical use in literature. The three correlation criteria are analyzed to establish their transversal relationships, and the theoretical analyses clearly indicate that the three correlation criteria are actually equivalent, which elegantly unifies these correlation criteria for pattern matching. Finally, the equivalence of these correlation criteria is further validated by numerical simulation and actual experiment.
IET Image Processing, 2012
Design and implementation of a new early termination algorithm for efficient calculation of correlation coefficient for template matching is presented. The proposed algorithm correlates the candidates against 'negative' (bit-inverted) version of reference instead of the original to implement a low cost early termination criterion. Around 10% computational savings have been demonstrated while using the proposed algorithm to compute normalised correlation as error metric for motion estimation in software implementation of H.264 video encoder. The algorithm lends itself to efficient hardware implementation because of its simple cost function. Further hardware savings have been realised by noting that the multiplication products generated by the proposed negative reference correlation algorithm tend to have low magnitudes with significantly less variance than those generated by other schemes. This allows a low-precision summation stage to accumulate majority of the multiplication products without losing the precision of results. Results of the hardware implementation on Xilinx Virtex-5 FPGA have been provided. The overall design is shown to consume around 85% less logic resources and operate at 140% higher speed than existing architectures.
Comparison of Local and Global Approaches to Digital Image Correlation
Experimental Mechanics, 2012
Local and global approaches to digital image correlation are compared when the displacement interpolation is based upon bilinear shape functions (i.e., with fournode quadrilaterals). The resolution in terms of displacements and strains associated with both techniques are evaluated a priori and validated a posteriori by using series of images of real experiments. It is shown that global approaches generally out-perform a local approach.
APPLICATION OF NORMALIZED CROSS CORRELATION TO IMAGE REGISTRATION
Image correspondence and registration techniques have gained popularity in recent times due to advancement of utilization in digital media and its storage. The main problem associated with image processing is when it is applied to fields like robotic vision and machine vision. The problem is due to clutter, i.e. the same frame with different objects has to be matched. Hence there has been need for efficient techniques of Image Registration. This led to development of feature extraction techniques and template matching techniques. The normalized cross correlation technique is one of them. A classical solution for matching two image patches is to use the cross-correlation coefficient. This works well if there is a lot of structure within the patches, but not so well if the patches are close to uniform. This means that some patches are matched with more confidence than others. By estimating this uncertainty more weight can be put on the confident matches than those that are more uncertain. All the simulations have been performed using MATLAB tool.