Image correlation is widely used for image and picture processing. Typical applications of image correlation are object location, image registration and sub-image similarity measurement. However, image correlation requires the comparison of a large number of sub-images implying a large computational effort that may prevent its use for real-time applications. On the other hand, correlation computation is very well suited for FPGA implementations. In this work we present efficient architectures for the implementation of Zero-Mean Normalized Cross-Correlation using FPGAs with application to image correlation. In particular, we compare the implementations of correlation in the spatial and spectral domains. Experimental results demonstrate that FPGAs improve performance by at least two orders of magnitude with respect to software implementations on a modern personal computer. This speed-up makes the performance of correlation computation suitable for real-time image processing. The proposed architectures have been applied to a correlation-based fingerprint-matching algorithm, demonstrating that real-time processing requirements can be well satisfied with an FPGA-based implementation.

High performance FPGA-based image correlation

https://escholarship.org/content/qt96b946g3/qt96b946g3.pdf?t=pqvu35

A characterization of a single-trial adaptive filter and its implementation in the frequency domain.

Droplet microfluidics has attracted significant interests in functional microcapsule synthesis, pharmaceuticals, fine chemicals, cosmetics and biomedical research. The low variability of performing chemical reactions inside droplets could benefit from improved homogeneity and reproducibility. Therefore, accurate and convenient methods are needed to monitor dynamic droplet generation processes. Here, a novel Cosine Similarity Algorithm (CSA) method was developed to monitor the droplet generation frequency accurately and rapidly. With a microscopic droplet generation video clip captured with a high-speed camera, droplet generation frequency can be computed accurately by calculating the cosine similarities between the frames in the video clip. Four kinds of dynamic droplet generation processes were investigated including (1) a stable condition in a single microfluidic channel, (2) a stable condition in multiple microfluidic channels, (3) a single microfluidic channel with artificial disturbances, and (4) microgel fabrication with or without artificial disturbances. For a video clip with 5,000 frames and a spatial resolution of 512 × 62 pixels, droplet generation frequency up to 4,707.9 Hz can be calculated in less than 1.70 s with an absolute relative calculation error less than 0.08%. Artificial disturbances in droplet generation processes can be precisely determined using the CSA method. This highly effective CSA method could be a powerful tool for further promoting the research of droplet microfluidics.

/pdf/a-cosine-similarity-algorithm-method-for-fast-and-accurate-27gc4swtes.pdf

A Cosine Similarity Algorithm Method for Fast and Accurate Monitoring of Dynamic Droplet Generation Processes

Calibration-Free Volume Flow Measurement Principle Based on Thermal Time-of-Flight (TToF)

A method of and apparatus for computing correlating images using the one dimensional Fast Fourier Transform (FFT) and the symmetry property of the Fourier Transform. In one aspect, the invention is a method of correlating images in the form of a pair of real number arrays. Apparatus for carrying the method out is also disclosed and claimed.

Method of and apparatus for improved image correlation

Fast Fourier transform (FFT) correlation is compared with direct discrete time (DDT) correlation of complex signals in terms of number of operations and memory requirements. The results establish criteria for evaluating which of the two techniques is the more economical in a real time application involving an indefinitely long input data sequence.

http://ieeexplore.ieee.org/iel5/5/31112/01448595.pdf

R.C. Borgioli

Papers

Fast Fourier transform correlation versus direct discrete time correlation