Power Spectrum Of Image Research Articles

Fingerprint Liveness Detection Based on Fake Finger Characteristics

The vitality detection of fingerprints is currently acknowledged as a serious issue for personal identity verification systems. This problem, raised some years ago, is related to the fact that the 3d shape pattern of a fingerprint can be reproduced using artificial materials. An image quite similar to that of true, alive, fingerprint, is derived if such “fake fingers” are submitted to an electronic scanner. Since introducing hardware dedicated to liveness detection in scanners is expensive, software-based solutions, based on image processing algorithms, have been proposed as alternative. So far, proposed approaches are based on features exploiting characteristics of a live finger (e.g., finger perspiration). Such features can be named live-based, or vitality-based features. In this paper, the authors propose and motivate the use of a novel kind of features exploiting characteristics noticed in the reproduction of fake fingers, that they named fake-based features. Then the authors propose a possibile implementation of this kind of features based on the power spectrum of the fingerprint image. The proposal is compared and integrated with several live-based features at the state-of-the-art, and shows very good liveness detection performances. Experiments are carried out on a data set much larger than commonly adopted ones, containing images from three different optical sensors.

Acoustic Measurements of Soil Pipeflow and Internal Erosion

Internal erosion of soil pipes can lead to embankment failures, landslides, and gully erosion. Therefore, non‐intrusive methods are needed to detect and monitor soil pipeflow and the resulting internal erosion. This paper presents a laboratory study using both active and passive acoustic techniques to monitor and assess soil pipeflow and internal erosion. A 140 cm long by 100 cm wide soil bed, 25‐cm deep contained a single 6 mm diam. soil pipe at 15‐cm depth that extended from an upper water reservoir to the lower bed face. The soil pipe was maintained under a constant head of 2 cm and the flow rate and sediment concentration measured at 15 s intervals while measuring soil water pressures at several locations within the bed every 30 s. Acoustic measurements were conducted every 5 s, which consisted of two parts: actively monitoring the acoustic wave propagation at four locations along the soil pipe and passively recording water flow sounds at one location. For active measurements, the phase slope method was employed to measure the P‐wave velocity under noisy and dynamic conditions. The study showed that the variation of the P‐wave velocity reflected the ongoing internal erosion processes such as the onset of soil pipeflow, the buildup of positive water pressures within the soil pipe, the saturation of soil adjacent to the pipe, the variation of water pressures within and adjacent to the soil pipe as the soil drained following removal of the constant head, and relaxation of the soil. These observations can be analyzed and understood by using the concept of the effective stress and its relationship with the P‐wave velocity. For passive measurements, passive signals (including water flow sounds and ambient noises) were recorded by a sensor buried inside the soil and close to the soil pipe. Three signal processing algorithms were applied for the passive signal analysis, which revealed similar temporal characteristic of the water flow sounds. The passive study suggested that soil pipeflow can be identified and assessed from sound levels in terms of time‐domain root mean square (TD‐RMS) and frequency‐domain root mean square (FD‐RMS) and from the contrasts of the power spectrum image.

Weft Weave Texture Feature Recognition Based on Power Spectrum

In this thesis, we apply Power Spectrum in fabric weave recognition, use power spectrum to analyze fabric image by image lightness features at definite illumination, and then extract fabric weave texture features. We can obtain fabric weave image power spectrum curve by Fourier Transform. From the curve, we can extract direction information of fabric weave, and get fabric weft density, then calculate weft Tex, weft number, weft repeats. Experiments prove the method practical and useful for fabric weave computer automatic analysis.

Improved Method of Target Detection on Optoelectronic Hybrid Joint Transform Correlator in Cluttered Scences

A classical joint transform correlator (JTC) usually yields large correlation sidelobes as well as a large correlation peak width, strong zero-order peak, and low diffraction efficiency, which make the detection ability of JTC lower. To overcome these difficulties, firstly, a joint power spectrum (JPS) subtraction technique in Fourier plane was proposed, where reference image power spectrum and object image power spectrum are subtracted from the JPS before inverse Fourier-transform operation, it is obvious that the modified JPS removes the zero-order term. Secondly, a fringe-adjusted filter (FAF) was presented to suppress sidelobes and noises. The modified JPS is multiplied by a FAF before the inverse Fourier-transform operation to obtain the cross-correlation peak. Computer simulations demonstrated the improved method can obviously remove zero-order diffraction and effectively suppress the sidelobes and noises compared with classic JTC, and then improve the detection ability for JTC. Experimental results presented the sharp correlation peak and also confirmed the method effectiveness.

Self adaptive high pass filtering using photochromic glass

We describe an auto programmable spatial-filtering system using photochromic glass plate as a programmable spatial light modulator, SLM, illuminated by a single wavelength of light. The proposed setup is a conventional 4f coherent optical system. At Fourier plane the filter function is written on the SLM as negative copy of the power spectrum of the input image. The method does not involve numerical processing, and thus, it could be potentially useful for processing large images. Validation experiments are presented.

Effect of detector lag on CT noise power spectra

The authors examined the effect of detector lag on the noise power spectrum (NPS) of CT images reconstructed with filtered backprojection (FBP). The authors derived an analytical expression of the NPS with detector lag, and then verified it using computer simulations with parallel beam and fan beam geometries. The dependence of the NPS on the amount of lag, location within the scanned field of view (FOV), and the number of views used in the reconstruction (samples per rotation) was investigated using constant and view dependent noise in the raw data. Detector lag introduces noise correlation in the azimuthal direction. The effect on the NPS is a frequency dependent reduction in amplitude. In small regions of the image, the effect is primarily in the frequencies corresponding to the azimuthal direction. The noise blurring and NPS filtering increases with increasing radial distance, and therefore regions at larger radial distances have lower noise power. With the same detector lag response function, the amount of noise correlation and NPS filtering decreases with increasing number of views. The shape of the NPS depends on the detector lag coefficients, location of the region, and the number of views used in the reconstruction. In general, the noise correlation caused by detector lag decreased the amplitude of the NPS.

Image displacement based on phase-encoded reference joint fractional transform correlator

In order to utilize the space of an input plane efficiently and make the optical structure more flexible, an image displacement measurement based on phase-encoded reference joint fractional transform correlator (PER-JFrTC) is proposed. We use a random phase mask to encode the reference image and overlay it with the target image forming the input image. Joint power spectrum (JPS) of the input image is obtained by Fourier transform and the resultant is encoded by the same phase mask. Then a fractional Fourier transform with an order p is applied to the phase-encoded JPS (PJPS), resulting in a correlation output with a sharp cross-correlation peak, which includes the displacement information between the reference and the target image. Contrast to displacement measurement based on traditional joint transform correlator (JTC), PER-JFrTC can use the space of the input plane efficiently and reduces the influence of the auto-correlation. Also the position of cross-correlation peak can be fixed arbitrarily according to the fractional order p as well as the optical set-up can be more flexible and easier to implement. Results based on digital computation show that PER-JFrTC could detect the displacement accurately and verify our proposal. A possible optical set-up is suggested.

Displacement measurement using phase-encoded target joint transform correlator

A displacement measurement technology using phase- encoded target joint transform correlator (PETJTC) is analyzed in detail. A phase mask is generated electronically and applied to encode the tar- get image. Input images include the phase-encoded target image and the reference image. The joint power spectrum of the input images are ob- tained and encoded by the same phase mask. Through another Fourier transform the brightest peak in relation to displacement between the ref- erence and target image appears in the correlation plane. In contrast to the displacement measurement based on traditional joint transform cor- relator, PETJTC could efficiently use the space of the input plane such as spatial light modulator, disperse the autocorrelation item into system noises, and leave the cross-correlation items only, which is convenient for detection. The effects of phase mask with different sizes and different types of noises are analyzed. Results based on digital computation show that PETJTC has a higher performance if the phase mask is bigger and has strong robustness under severe noise. Different displacement mea- surement technologies are contrasted. PETJTC could accurately detect the displacement. Root mean square errors can remain within 0.1 pixel. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). (DOI: 10.1117/1.3552661) Subject terms: image stabilization; displacement measurement; joint transform correlator; phase-encoded.

画像のサブバンド符号化における符号化レートに応じた最適帯域分割

In subband image coding, the optimum frequency band partition was previously proposed on the basis of the power spectrum of an input image. However, the partition pattern on the 2-D frequency domain was invariable when the bit rate changed. Therefore, a new optimum frequency band partition has been developed that can determine both the partition pattern on the 2-D frequency domain and the combination of quantizers with subband signals for the given bit rate. The experimental results show that the proposed method improved the coding performances at the lower bit rate compared with the conventional method.

Rapid scalar value classification and volume clipping for interactive 3D medical image visualization

In many clinical scenarios, medical data visualization and interaction are important to physicians for exploring inner anatomical structures and extracting meaningful diagnostic information. Real-time high-quality volume rendering, artifact-free clipping, and rapid scalar value classification are important techniques employed in this process. Unfortunately, in practice, it is still difficult to achieve an optimal balance. In this paper, we present some strategies to address this issue, which are based on the calculation of segment-based post color attenuation and dynamic ray–plane intersection (RPI) respectively. When implemented within our visualization system, the new classification algorithm can deliver real-time performance while avoiding the “color over-accumulation” artifacts suffered by the commonly used acceleration algorithms that employ pre-integrated classification. Our new strategy can achieve an optimized balance between image quality and classification speed. Next, the RPI algorithm is used with opacity adjustment technique to effectively remove the “striping” artifacts on the clipping plane caused by the nonuniform integration length. Furthermore, we present techniques for multiple transfer function (TF) based anatomical feature enhancement and “keyhole” based endoscopic inner structure view. Finally, the algorithms are evaluated subjectively by radiologists and quantitatively compared using image power spectrum analysis.

High-DQE EPIDs based on thick, segmented BGO and CsI:Tl scintillators: performance evaluation at extremely low dose.

Electronic portal imaging devices (EPIDs) based on active matrix, flat-panel imagers (AMFPIs) have become the gold standard for portal imaging and are currently being investigated for megavoltage cone-beam computed tomography (CBCT) and cone-beam digital tomosynthesis (CBDT). However, the practical realization of such volumetric imaging techniques is constrained by the relatively low detective quantum efficiency (DQE) of AMFPI-based EPIDs at radiotherapy energies, approximately 1% at 6 MV. In order to significantly improve DQE, the authors are investigating thick, segmented scintillators, consisting of 2D matrices of scintillating crystals separated by septal walls. A newly constructed segmented BGO scintillator (11.3 mm thick) and three segmented CsI:Tl scintillators (11.4, 25.6, and 40.0 mm thick) were evaluated using a 6 MV photon beam. X-ray sensitivity, modulation transfer function, noise power spectrum, DQE, and phantom images were obtained using prototype EPIDs based on the four scintillators. The BGO and CsI:Tl prototypes were found to exhibit improvement in DQE ranging from approximately 12 to 25 times that of a conventional AMFPI-based EPID at zero spatial frequency. All four prototype EPIDs provide significantly improved contrast resolution at extremely low doses, extending down to a single beam pulse. In particular, the BGO prototype provides contrast resolution comparable to that of the conventional EPID, but at 20 times less dose, with spatial resolution sufficient for identifying the boundaries of low-contrast objects. For this prototype, however, the BGO scintillator exhibited an undesirable radiation-induced variation in x-ray sensitivity. Prototype EPIDs based on thick, segmented BGO and CsI:T1 scintillators provide significantly improved portal imaging performance at extremely low dose (i.e., down to 1 beam pulse corresponding to approximately 0.022 cGy), creating the possibility of soft-tissue visualization using MV CBCT and CBDT at clinically practical dose.

Real Space and Wave‐Number Space Studies of the Phase Structure and Morphology of iPP/PEOc Blends Using Scanning Electron Microscopy

AbstractThe influence of blend composition on the phase structure and morphology of poly(propylene)/poly(ethylene‐co‐octene) blends was studied using SEM. A diameter dg was defined and calculated in real space to discuss the phase structure and morphology of iPP/PEOc blends. The figure‐estimation method was introduced to determine the distribution width of dg. It was shown that the distribution of dg obeys a log‐normal distribution and the distribution width σ of dg was calculated. In wave‐number (h) space, the correlation distance, ac, was defined by applying light scattering theory to power spectrum images obtained by 2D Fourier transformation. Moreover, a fractal dimension, Dc, was introduced to describe the uniformity of the spatial distribution.magnified image

Fake-fingerprint detection using multiple static features

Recently, fake fingerprints have become a serious concern for the use of fingerprint recognition systems. We introduce a novel fake-fingerprint detection method that uses multiple static features. With regard to the usability of the method for field applications, we employ static features extracted from one image to determine the aliveness of fingerprints. We consider the power spectrum, histogram, directional contrast, ridge thickness, and ridge signal of each fingerprint image as representative static features. Each feature is analyzed with respect to the physiological and statistical distinctiveness of live and fake fingerprints. These features form a feature vector set and are fused at the feature level through a support vector machine classifier. For performance evaluation and comparison, a total of 7200 live images and 9000 fake images were collected using four sensors (three optical and one capacitive). Experimental results showed that proposed method achieved approximately 1.6% equal-error rate with optical-based sensors. In the case of the capacitive sensor, there was no test error when only one image was used for a decision. Based on these results, we conclude that the proposed method is a simple yet promising fake-fingerprint inspection technique in practice.

Estimation of grain-size distributions and associated parameters from digital images of sediment

A new technique to estimate the grain-size distribution (GSD) from a digital image of sediment is proposed, advancing the applicability of a suite of sedimentary ‘look-up-catalogue’ approaches originated by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160–165]. The outputs of an automated procedure to estimate the GSD from digital images of sediment are examined with reference to the distributions obtained from both manually sieving the corresponding sediment samples, and axial measurements made on the grains in the images. Measures of grain-size obtained from the imaging procedure correlate very well with grain-size measures derived from both the number-frequency and mass-frequency curve. As expected the GSD obtained from the new automated approach, based on kernel density, compared better with point counts because of a shared two-rather than three-dimensionality. The GSD shape is not always mimicked exactly, however the percentiles obtained from the cumulative GSD compare well with those from sieved distributions, which allow for the first time computation of graphical sorting and skewness from digital images of sediment which are accurate reflections of those measures obtained for point-count and sieved samples. The new approach allows for realistic GSDs from which the residual can be computed, thus a numerical criterion upon which the grain-size distribution from an image can be accepted or rejected. Finally, a method is presented whereby two-dimensional autocorrelogram fields are derived from image power spectra. Ellipsoids are fitted to isolines of autocorrelation coefficients, and from this the dominant axial lengths and orientation of these isolines which could facilitate computation of major and minor axis lengths of grains in sample images, as well as their dominant orientation. In turn, this could allow for parameterisation of axial ratios for parameterisation of 2D shape. Such analysis is completely automated, rapid and non-intrusive.

Developing a new method to assess poor visibility level on roads by digital images

This study proposes a new index for estimating visibility under poor-visibility conditions by using digital images from a road monitoring camera. The method allows representation of the amount of visual information based on human spatial frequency characteristics. A laboratory experiment was performed in 2002 under artificial fog. We examined the weighted intensity of power spectra (WIPS) to determine its applicability as a visibility assessment value. The magnitude of WIPS represented the difference in spatial frequencies within the image based on human contrast sensitivity function. WIPS was calculated from the following image-processing procedure. As an initial step, a box measuring 128 × 128 pixels was cut from the original image. The spatial frequency of the cutout image was calculated using two-dimensional Fourier transform, and the power spectrum of the cutout image was calculated. We totaled the WIPS at five spatial frequencies (cycles per degree, cpd): 1.5 cpd, 3 cpd, 6 cpd, 12 cpd and 18 cpd. WIPS were compared with the subjective visibility assessment values (SVAV) given by test subjects. There was a clear relationship between WIPS and total SVAV: WIPS increased as total SVAV increased. These results suggest that WIPS might be an appropriate index for estimating visibility using digital images.

“Whitenedfaces” Recognition With PCA and ICA

This letter develops a simple and effective whitening method for flattening the power-law power spectrum of face images and combines the whitening technique and PCA/ICA for face recognition. The whitening parameter in the whitening filter is adaptive to the input data so as to make the power spectrum of the whitened results as flat as possible. This proposed method is computationally saving for using fast Fourier transform algorithms. The transformed ldquowhitenedfacesrdquo are applied to face recognition with PCA and ICA coding strategies, respectively. The results show that the whitening processing will bring better recognition performances for both PCA and ICA representations.

X-ray imaging with the PILATUS 100k detector

We report on the application of the PILATUS 100K pixel detector for medical imaging. Experimental results are presented in the form of X-ray radiographs using standard X-ray absorption contrast and a recently developed phase contrast imaging method. The results obtained with the PILATUS detector are compared to results obtained with a conventional X-ray imaging system consisting of an X-ray scintillation screen, lens optics, and a charge coupled device. Finally, the results for both systems are discussed more quantitatively based on an image power spectrum analysis.

Prediction of panellists’ perception of bread crumb appearance using fractal and visual textural features

Ratings of visual characteristics of bread crumb images obtained by panellists were correlated with features obtained by digital fractal and texture analysis and simple thresholding. Trained panellists were asked to rate 168 bread crumb images on fineness, homogeneity and degree of orientation, using continuous line scales. The relative orientation of the main and secondary peaks of the image power spectrum was the only parameter related to the human perception of the degree of crumb orientation. Single fractal dimension terms correlated better with the panellists’ perception of grain fineness and homogeneity than the single crumb features from thresholding. Second-order polynomial models were significantly better (P 0.860).

Rotation- and scale-invariant texture features based on spectral moment invariants

Moment invariants previously developed for the analysis of two-dimensional patterns and objects regardless of orientation, scale, and position are extended to the Fourier transform domain to quantify signatures of textures in the power spectrum of images. The moment invariants of the power spectrum, which we call spectral moment invariants (SMIs), systematically extract rotation- and scale-invariant texture features by complex spectral moments instead of by performing ad hoc measurements of the shape of the two-dimensional power spectrum as do most of the existing Fourier transform domain methods. To our knowledge, the method of using SMIs to quantify texture features is the first to extract invariant texture information directly from the Fourier spectrum. The discriminative capability of SMIs in recognizing rotation- and scale-independent texture features is demonstrated by texture classification experiments. The results indicate that algorithms using SMIs can achieve performances comparable with, or better than, those algorithms using the spatial or wavelet transform domain texture features.

Determination of astigmatism in TEM images

We have developed a new two-step algorithm to determine the astigmatism of images from transmission electron microscopes (TEMs). Instead of computing the radial average of the power spectrum, we divide the power spectrum of a TEM image 1 to m (typically 32) sectors. We use a technique based on perturbation analysis of the contrast transfer function (CTF) to assimilate sector averages of the power spectrum of an image, which are incoherent in the presence of astigmatism, to a coherent radial average corresponding to a nominal defocus value. This is based on the fact that small defocus change from a nominal value can be considered to be equivalent to a perturbation on the spatial frequency spectra. Thus, instead of measuring the angular defocus variations, we optimise the frequency change required to obtain a coherent radial average. Numerically, this is achieved by minimizing σ 2/ σ 1 of a matrix formed from the sector averages, where σ i denotes the ith singular value of the matrix. After the minimisation procedure, the second singular value should be very small compared with the first singular value, indicating that the matrix is nearly rank unity. In the second step, the nominal defocus can be obtained from the coherent radial average using any good defocus estimation program, which assumes zero astigmatism. The defocus value at a sector can be obtained from this nominal defocus value and one of the parameters from the unconstrained optima. Our algorithm is tested on astigmatic images of carbon film, 2D crystals of bacteriorhodopsin and cryo-images of HIV cores.