Invariant pattern recognition by use of a spatial code division multiplexing approach

Invariant pattern recognition can be achieved by use of harmonic decomposition, for example circular harmonics are used for rotation invariant recognition. A common problem with such methods is that often only a single term of the harmonic decomposition is used, and it does not contain a sufficient amount of the reference energy. Thus discrimination capability is limited, especially in the presence of noise or other disturbances. By using several terms of the harmonic decomposition together this problem can be solved; this can be achieved by the use of code division filter multiplexing. Several harmonic terms are encoded onto a single filter, and the signal is simultaneously correlated with all of them, hence producing enhanced discrimination capabilities. Here two methods are suggested for such encoding. The first involves multiplexing the filters in the Fourier plane, while the second involves multiplexing in the image plane.     

Multiple circular-harmonic-function correlation filter providing specified response to in-plane rotation

The circular-harmonic-function correlation filter originally proposed by Hsu and Arsenault [Appl. Opt. 21, 4016 (1982)] for in-plane rotation invariance uses only one harmonic, which results in poor discrimination capability of the filter. Various methods to use multiple harmonics were explored previously by different researchers. We present a new method to combine multiple circular harmonics into a single filter that can provide the desired correlation response to in-plane rotation while minimizing the correlation-plane energy. Since multiple harmonics are included, the filter can discriminate well, and since correlation-plane energy is minimized, correlation peaks tend to be sharp. Since the designer can specify the desired in-plane rotation response, a variety of filter behaviors (including complete invariance to input rotations) can be obtained. Underlying theory is discussed, and simulation results are presented.     

Scale and translation invariant minimum average correlation energy filter

A new type, to our knowledge, of scale and translation invariant correlation filter is described. Its form in polar coordinates generalizes the forms of the one-decomposition-term filters. That is combined with the minimum-average-correlation-energy optimization method to suppress the sidelobes and achieve correlation peaks. A theoretical analysis as well as a detailed explanation of the computational procedure is provided. The concept is tested on five interferometric images of 256 gray levels without preprocessing. The computed filter gives correlation peaks for reference image scales in the range of 0.3/4.0 (minimal scale: maximal scale = 1:13). The discrimination ability of the filter is investigated-no false peak occurred. The filter works in the background so that there is no need for input image segmentation. A method for extension is described to calculate a filter for more than one reference image.     

Generation of non-Gaussian stochastic processes using nonlinear filters

Non-Gaussian stochastic processes are generated using nonlinear filters in terms of Itô differential equations. In generating the stochastic processes, two most important characteristics, the spectral density and the probability density, are taken into consideration. The drift coefficients in the Itô differential equations can be adjusted to match the spectral density, while the diffusion coefficients are chosen according to the probability density. The method is capable to generate a stochastic process with a spectral density of one peak or multiple peaks. The locations of the peaks and the band widths can be tuned by adjusting model parameters. For a low-pass process with the spectrum peak at zero frequency, the nonlinear filter can match any probability distribution, defined either in an infinite interval, a semi-infinite interval, or a finite interval. For a process with a spectrum peak at a non-zero frequency or with multiple peaks, the nonlinear filter model also offers a variety of profiles for probability distributions. The non-Gaussian stochastic processes generated by the nonlinear filters can be used for analysis, as well as Monte Carlo simulation.     

A multi-band shunt hybrid active filter with reduced sensor count

A Shunt Hybrid Active Filter (SHAF) is an attractive option for realizing low-cost harmonic compensation solutions. This paper proposes a SHAF with multiple harmonic compensation capability using a single Voltage Source Inverter and reduced sensor count. This strategy is apt for harmonic filtering solutions where low cost is the exclusive priority. In this paper, a new estimation approach is proposed to obviate requirement of a large number of sensors. Multiple Synchronous Reference Frames (MSRF) and low pass filters are used to measure 5^th and 7^th harmonic components separately from load as well as filter currents. Individual current controllers are designed for the 5^th and 7^th harmonic currents. Control is realized in the synchronously rotating, orthogonal (dq) reference frame. Performance of the controller is validated through simulation, using realistic plant and controller models. Experimental results are provided to corroborate the analytical and simulation results.     

Shift and scale‐invariant correlation for pattern recognition based on the bidimensional empirical mode decomposition with noise robustness

Abstract

A novel filter is proposed to improve the noise robustness and discrimination capability for shift and scale invariant pattern recognition. This filter is a combination of mellin radial harmonic filter (RHF) and the bidimensional empirical mode decomposition. The basic principle of this method is to make use of partial reconstructions of the image by the relevant intrinsic mode functions corresponding to the most important structures of the image. A criterion is proposed to determine the proper number of intrinsic mode functions to be discarded for denoising by discussing the characteristic of the noise. The proposed filter provides a wider allowable scale change of the object. Within this range, the correlation peak intensity is relatively uniform even in the case of noise. This proposed filter has been tested experimentally to confirm the result from numerical simulations for cases with and without additive white Gaussian noise.     

Improved Matched Filter Based on Radial Eigenfunctions

Abstract

A new rotation invariant filter is proposed. The Karhunen-Loeve (KL) expansion is used to find a set of radial eigenfunctions corresponding to a target. A pseudo-object is reconstructed by the inverse KL transform using a reduced number of those functions. The rotation-invariant filter using radial eigenfunctions is obtained with the use of the circular harmonic decomposition of the pseudo-object. A computer simulation shows that this filter gives good results for discrimination and pattern recognition in the presence of a cluttered background.     

Convolution-kernel-based optimal trade-off filters for optical pattern recognition

An architecture for the implementation of optical pattern recognition is proposed that makes use of convolution-kernel-based optimal trade-off filters to allow for an increased speed of operation and filter storage capability. The derivation of these new convolution-kernel-based optimal trade-off filters is presented, and their noise robustness and discrimination capabilities are discussed.     

Constrained quadratic correlation filters for target detection

A method for designing and implementing quadratic correlation filters (QCFs) for shift-invariant target detection in imagery is presented. The QCFs are quadratic classifiers that operate directly on the image data without feature extraction or segmentation. In this sense the QCFs retain the main advantages of conventional linear correlation filters while offering significant improvements in other respects. Not only is more processing required for detection of peaks in the outputs of multiple linear filters but choosing the most suitable among them is an error-prone task. All channels in a QCF work together to optimize the same performance metric and to produce a combined output that leads to considerable simplification of the postprocessing scheme. The QCFs that are developed involve hard constraints on the output of the filter. Inasmuch as this design methodology is indicative of the synthetic discriminant function (SDF) approach for linear filters, the filters that we develop here are referred to as quadratic SDFs (QSDFs). Two methods for designing QSDFs are presented, an efficient architecture for achieving them is discussed, and results from the Moving and Stationary Target Acquisition and Recognition synthetic aperture radar data set are presented.     

Log-polar transform-based wavelet-modified maximum average correlation height filter for distortion invariance in a hybrid digital-optical correlator

We discuss and implement a log-polar transform-based distortion-invariant filter for automatic target recognition applications. The log-polar transform is a known space-invariant image representation used in several image vision systems to eliminate the effects of scale and rotation in an image. For in-plane rotation invariance and scale invariance, a log-polar transform-based filter was synthesized. In cases of in-plane rotation invariance, peaks shift horizontally, and in cases of scale invariance, peaks shift vertically. To achieve out-of-plane rotation invariance, log-polar images were used to train the wavelet-modified maximum average correlation height (WaveMACH) filter. The designed filters were implemented in the hybrid digital-optical correlation scheme. It was observed that, for a certain range of rotation and scale differences, the correlation signals merge with the strong dc. To solve this problem a shift was introduced in the log-polar image of the target. The use of a chirp function for dc removal has also been discussed. Correlation peak height and peak-to-sidelobe ratio have been calculated as metrics of goodness of the log-polar transform-based WaveMACH filter. Experimental results are presented.     

Rotation-invariant discrimination between almost similar objects

A modified circular harmonic filter may be used for the rotation-invariant discrimination of a target from another object which contains the same pattern as the target. The method is illustrated by the experimental rotation-invariant detection of the letter F in the presence of the letter E.     

Performance of minimum-mean-square-error filters for spatially nonoverlapping target and input-scene noise

Using computer simulations, we investigate the performance of a minimum-mean-square-error filter for input-scene noise that is spatially nonoverlapping (disjoint) with a target for a limited set of images. Different input-scene-noise statistics are used to test the filter performance. We show that in the presence of spatially nonoverlapping target and input-scene noise, the output of the minimummean- square-error filter has a well-defined correlation peak, small sidelobes, and a high peak-to-correlationenergy ratio compared with other widely used filters such as the classical matched filter, the phase-only filter, and the inverse filter. We also test the robustness of the minimum-mean-square-error filter to errors in noise statistics used in the filter design. We show that, for the images tested here, the performance of the minimum-mean-square-error filter is not sensitive to errors in noise statistics and the filter can detect the target even if a considerable error exists. The discrimination capability and the illumination sensitivity of the minimum-mean-square-error filter are also tested.     

Hybrid digital-optical correlation employing a chirp-encoded simulated-annealing-based rotation-invariant and distortion-tolerant filter

The simulated annealing (SA) algorithm based on entropy optimization is a technique of synthesizing distortion-invariant matched filters capable of discriminating very similar images. The synthesis of rotation-invariant filters using modified SA-based filter equations and their tolerance to distortions are studied. The filters are trained with true class images rotated in-plane at 3 degrees intervals between 0 degrees and 360 degrees . A total of seven filters are required over the whole range for both CCD or thermal images. Optical correlation in a hybrid digital-optical correlator results in an unwanted zero-order dc along with two first-order (+/-1) correlation peaks. A chirp function multiplied with the filter separates out the three peaks to three different planes, and only one peak in focus is captured in a camera. The performance of the modified SA-based filter has been studied in comparison to the conventional SA filter as well as with other filters.     

Post-beamforming second-order Volterra filter for pulse-echo ultrasonic imaging

We present a new algorithm for deriving a second-order Volterra filter (SVF) capable of separating linear and quadratic components from echo signals. Images based on the quadratic components are shown to provide contrast enhancement between tissue and ultrasound contrast agents (UCAs) without loss in spatial resolution. It is also shown that the quadratic images preserve the low scattering regions due to their high dynamic range when compared with standard B-mode or harmonic images. A robust algorithm for deriving the filter has been developed and tested on real-time imaging data from contrast and tissue-mimicking media. Illustrative examples from image targets containing contrast agent and tissue-mimicking media are presented and discussed. Quantitative assessment of the contrast enhancement is performed on both the RF data and the envelope-detected log-compressed image data. It is shown that the quadratic images offer levels of enhancement comparable or exceeding those from harmonic filters while maintaining the visibility of low scattering regions of the image.     

Self-aligned spatial filtering using laser optical tweezers

We present an optical spatial filtering device that has been integrated into a microfluidic system and whose motion and alignment is controlled using a laser optical tweezer. The lithographically patterned micro-optical spatial filter device filters out higher frequency additive noise components by automatically aligning itself in three dimensions to the focus of the laser beam. This self-alignment capability is achieved through the attachment of a refractive optical element directly over the circular aperture or pinhole of the spatial filter. A discussion of two different spatial filter designs is presented along with experimental results that demonstrate the effectiveness of the self-aligned micro-optic spatial filter.     

Incoherent pattern detection using a liquid-crystal active lens

Incoherent pattern detection by a simple imaging system using a liquid-crystal active lens is proposed. The imaging system works as a spatial filtering system with a rewritable phase-only filter. We found that, in the incoherent matched filtering system, a conventional phase-only filter has a higher optical efficiency but a lower pattern discrimination than a complex filter. To improve the pattern discrimination ability, we optimized the phase-only filter by using simulated annealing and a genetic algorithm. We designed phase-only filters that have discrimination ability comparable with that in a complex filter. The performance of optimized phase-only filters is experimentally demonstrated.     

Filter for biomedical imaging and image processing

Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a priori, knowledge about the type of noise corrupting the image. This makes the standard filters application specific. Widely used filters such as average, Gaussian, and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high-frequency details, making the image nonsmooth. An integrated general approach to design a finite impulse response filter based on Hebbian learning is proposed for optimal image filtering. This algorithm exploits the interpixel correlation by updating the filter coefficients using Hebbian learning. The algorithm is made iterative for achieving efficient learning from the neighborhood pixels. This algorithm performs optimal smoothing of the noisy image by preserving high-frequency as well as low-frequency features. Evaluation results show that the proposed finite impulse response filter is robust under various noise distributions such as Gaussian noise, salt-and-pepper noise, and speckle noise. Furthermore, the proposed approach does not require any a priori knowledge about the type of noise. The number of unknown parameters is few, and most of these parameters are adaptively obtained from the processed image. The proposed filter is successfully applied for image reconstruction in a positron emission tomography imaging modality. The images reconstructed by the proposed algorithm are found to be superior in quality compared with those reconstructed by existing PET image reconstruction methodologies.     

Narrowband multichannel filters and integrated optical filter arrays

We propose and demonstrate three approaches to achieve narrowband multichannel filters. These are multiple heterostructures with defects, guided-mode resonance (GMR) Brewster filters with multiple channels, and integrated narrow bandpass filter arrays. Transmission studies for multiple heterostructures with defects are presented. We show that the enlargement of the forbidden band and multiple-channel filtering can be reached simultaneously with these configurations. GMR Brewster filters with multiple channels can be obtained with a single-layer grating. The same properties can be obtained by use of double-layer structures that consist of a homogeneous layer and a grating with equal refractive index. We developed a combinatorial etching technique that has 32 elements on a single substrate with which to fabricate integrated narrow bandpass filters. Single- and double-chamber integrated optical filter arrays were fabricated by use of this etching technique. These narrowband multichannel filters and narrow bandpass filter arrays show good filtering features and can be utilized in many optical applications.     

Large value AC capacitor for harmonic filtering and reactive power compensation

To overcome the limitations of conventional shunt passive filters, which are invariably used for harmonic filtering, a quasi-passive filter (QPF) has been proposed. It comprises a parallel and series tuned LC tank circuit. Unlike the conventional shunt passive filter, the QPF utilises a large value AC capacitor. Unipolar DC capacitors and power semiconductor devices have been used to realise the large value AC capacitor. The operation of the QPF is simple and it does not require the complex control methods of active power filters. With certain modifications in the QPF, a modified quasi-passive filter (MQPF) has been proposed, which can be used for reactive power compensation in addition to harmonic filtering. The proposed QPF and MQPF have been verified through analysis and simulation. Experiments are carried out to verify the validity of the QPF.     

Rotation invariant color pattern recognition by use of a three-dimensional Fourier transform

Recently, the use of three-dimensional correlation for multichannel pattern recognition has been introduced. In this work we propose the use of circular harmonic components with this new technique to obtain invariance under target rotations. The differences between this method and the previous use of circular harmonic filters for multichannel images are discussed. Also the problem of determining the proper center is studied and, to our knowledge, a new and more understandable criterion to locate it is introduced. Some simulation results to verify the successful operation of the method are included.