Robust image hashing using higher order spectral features

Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.

Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

Position, rotation, and scale invariant recognition of images using higher-order spectra

A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies

Radioactive residues associated with water treatment, use and disposal in Australia

Water resources are known to contain radioactive materials, either from natural or anthropogenic sources. Treatment, including wastewater treatment, of water for drinking, domestic, agricultural and industrial purposes has the potential to concentrate radioactive materials. Inevitably concentrated radioactive material is discharged to the environment as a waste product, reused for soil conditioning, or perhaps recycled as a new potable water supply. This thesis, presented as a collection of peer reviewed scientific papers, explores a number of water / wastewater treatment applications, and the subsequent nature and potential impact of radioactive residues associated with water exploitation processes. The thesis draws together research outcomes for sites predominantly throughout Queensland, Australia, where it is recognised that there is a paucity of published data on the subject. This thesis contributes to current knowledge on the monitoring, assessment and potential for radiation exposure from radioactive residues associated with the water industry.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

Robust image hash functions using higher order spectra

Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

Inflammation in lung carcinogenesis

It was Dvorak in 1986 that postulated 'tumours are wounds that do not heal' as they share common cellular and molecular mechanisms, which are active in both wounds and in cancer tissue. Inflammation is a crucial part of the innate immune system that protects against pathogens and initiates adaptive immunity. Acute inflammation is usually a rapid and self-limiting process, however it does not always resolve. This leads to the establishment of a chronic inflammatory state and provides the perfect environment for carcinogenesis. Inflammation and cancer have long had an association, going back as far as Virchow in 1863, when leucocytes were noted in neoplastic tissue. It has been estimated that approximately 25% of all malignancies are initiated or exacerbated by inflammation caused by infectious agents. Furthermore, inflammation is linked to all of the six hallmarks of cancer (evasion of apoptosis, insensitivity to anti-growth signals, unlimited replicative potential, angiogenesis, increase in survival factors and invasion and metastasis). It is thought that inflammation may play a critical role in lung carcinogenesis given that individuals with inflammatory lung conditions have an increased risk of lung cancer development. Cigarette smoking can also induce inflammation in the lung and smokers are at a higher risk of developing lung cancer than non-smokers. However, exposure to a number of environmental agents such as radon, have also been demonstrated as a causative factor in this disease. This chapter will focus on inflammation as a contributory factor in non small cell lung cancer (NSCLC), concentrating primarily on the pathological involvement of the pro-inflammatory cytokines, TNF-α, IL-1β, and the CXC (ELR+) chemokine family. Targeting of inflammatory mediators will also be discussed as a therapeutic strategy in this disease. © 2013 by Nova Science Publishers, Inc. All rights reserved.

Chronic activation of the low affinity site of β1-adrenoceptors stimulates haemodynamics but exacerbates pressure-overload cardiac remodelling

Background and Purpose The β1-adrenoceptor has at least two binding sites, high and low affinity sites (β1H and β1L, respectively), which mediate cardiostimulation. While β1H-adrenoceptor can be blocked by all clinically used β-blockers, β1L-adrenoceptor is relatively resistant to blockade. Thus, chronic β1L-adrenoceptor activation may mediate persistent cardiostimulation, despite the concurrent blockade of β1H-adrenoceptors. Hence, it is important to determine the potential significance of β1L-adrenoceptors in vivo, particularly in pathological situations. Experimental Approach C57Bl/6 male mice were used. Chronic (4 or 8 weeks) β1L-adrenoceptor activation was achieved by treatment, via osmotic mini pumps, with (-)-CGP12177 (10 mg·kg−1·day−1). Cardiac function was assessed by echocardiography and micromanometry. Key Results (-)-CGP12177 treatment of healthy mice increased heart rate and left ventricular (LV) contractility. (-)-CGP12177 treatment of mice subjected to transverse aorta constriction (TAC), during weeks 4–8 or 4–12 after TAC, led to a positive inotropic effect and exacerbated fibrogenic signalling while cardiac hypertrophy tended to be more severe. (-)-CGP12177 treatment of mice with TAC also exacerbated the myocardial expression of hypertrophic, fibrogenic and inflammatory genes compared to untreated TAC mice. Washout of (-)-CGP12177 revealed a more pronounced cardiac dysfunction after 12 weeks of TAC. Conclusions and Implications β1L-adrenoceptor activation provides functional support to the heart, in both normal and pathological (pressure overload) situations. Sustained β1L-adrenoceptor activation in the diseased heart exacerbates LV remodelling and therefore may promote disease progression from compensatory hypertrophy to heart failure.

Performance degradation in feedback control due to constraints

In this note, we present a method to characterize the degradation in performance that arises in linear systems due to constraints imposed on the magnitude of the control signal to avoid saturation effects. We do this in the context of cheap control for tracking step signals.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

Genetic evidence for natural hybridization between Red Snow Crab (Chionoecetes japonicus) and Snow Crab (Chionoecetes opilio) in Korea

Both red snow crab (Chionoecetes japonicus Rathbun, 1932) and snow crab (Chionoecetes opilio Fabricius, 1788) are commercially important species in Korea. The geographical ranges of the two species overlap in the East Sea, where both species are fished commercially. Morphological identification of the two species and putative hybrids can be difficult because of their overlapping morphological characteristics. The presence of putative hybrids can affect the total allowable catch (TAC) of C. japonicus and C. opilio, and causes problems managing C. japonicus and C. opilio wild resources. To date, however, no natural hybridization has been reported between C. japonicus and C. opilio, despite their overlapping distributions along the coast of the East Sea. In this study, the internal transcribed spacer (ITS) region of major ribosomal RNA genes from the nuclear genome and the cytochrome oxidase I (CO I) gene from the mitochondrial genome were sequenced to determine whether natural hybridization occurs between the two species. Our results revealed that all putative hybrids identified using morphological traits had two distinct types of ITS sequences corresponding to those of both parental species. Mitochondrial CO I gene sequencing showed that all putative hybrids had sequences identical to C. japonicus. A genotyping assay based on single nucleotide polymorphisms in the ITS1 region and the CO I gene produced the most efficient and accurate identification of all hybrid individuals. Molecular data clearly demonstrate that natural hybridization does occur between C. japonicus and C. opilio, but only with C. japonicus as the maternal parent.

Indoor Air Quality in Naturally Ventilated Italian Classrooms

Characterization of indoor air quality in school classrooms is crucial to children’s health and performance. The present study was undertaken to characterize the indoor air quality in six naturally ventilated classrooms of three schools in Cassino (Italy). Indoor particle number, mass, black carbon, CO2 and radon concentrations, as well as outdoor particle number were measured within school hours during the winter and spring season. The study found the concentrations of indoor particle number were influenced by the concentrations in the outdoors; highest BC values were detected in classrooms during peak traffic time. The effect of different seasons’ airing mode on the indoor air quality was also detected. The ratio between indoor and outdoor particles was of 0.85 ± 0.10 in winter, under airing conditions of short opening window periods, and 1.00 ± 0.15 in spring when the windows were opened for longer periods. This was associated to a higher degree of penetration of outdoor particles due to longer period of window opening. Lower CO2 levels were found in classrooms in spring (908 ppm) than in winter (2206 ppm). Additionally, a greater reduction in radon concentrations was found in spring. In addition, high PM10 levels were found in classrooms during break time due to re-suspension of coarse particles. Keywords: classroom; Ni/Nout ratio; airing by opening windows; particle number

Hydrogen soil deposition and atmospheric variations in the boreal zone

This research has been prompted by an interest in the atmospheric processes of hydrogen. The sources and sinks of hydrogen are important to know, particularly if hydrogen becomes more common as a replacement for fossil fuel in combustion. Hydrogen deposition velocities (vd) were estimated by applying chamber measurements, a radon tracer method and a two-dimensional model. These three approaches were compared with each other to discover the factors affecting the soil uptake rate. A static-closed chamber technique was introduced to determine the hydrogen deposition velocity values in an urban park in Helsinki, and at a rural site at Loppi. A three-day chamber campaign to carry out soil uptake estimation was held at a remote site at Pallas in 2007 and 2008. The atmospheric mixing ratio of molecular hydrogen has also been measured by a continuous method in Helsinki in 2007 - 2008 and at Pallas from 2006 onwards. The mean vd values measured in the chamber experiments in Helsinki and Loppi were between 0.0 and 0.7 mm s-1. The ranges of the results with the radon tracer method and the two-dimensional model were 0.13 - 0.93 mm s-1 and 0.12 - 0.61 mm s-1, respectively, in Helsinki. The vd values in the three-day campaign at Pallas were 0.06 - 0.52 mm s-1 (chamber) and 0.18 - 0.52 mm s-1 (radon tracer method and two-dimensional model). At Kumpula, the radon tracer method and the chamber measurements produced higher vd values than the two-dimensional model. The results of all three methods were close to each other between November and April, except for the chamber results from January to March, while the soil was frozen. The hydrogen deposition velocity values of all three methods were compared with one-week cumulative rain sums. Precipitation increases the soil moisture, which decreases the soil uptake rate. The measurements made in snow seasons showed that a thick snow layer also hindered gas diffusion, lowering the vd values. The H2 vd values were compared to the snow depth. A decaying exponential fit was obtained as a result. During a prolonged drought in summer 2006, soil moisture values were lower than in other summer months between 2005 and 2008. Such conditions were prevailing in summer 2006 when high chamber vd values were measured. The mixing ratio of molecular hydrogen has a seasonal variation. The lowest atmospheric mixing ratios were found in the late autumn when high deposition velocity values were still being measured. The carbon monoxide (CO) mixing ratio was also measured. Hydrogen and carbon monoxide are highly correlated in an urban environment, due to the emissions originating from traffic. After correction for the soil deposition of H2, the slope was 0.49±0.07 ppb (H2) / ppb (CO). Using the corrected hydrogen-to-carbon-monoxide ratio, the total hydrogen load emitted by Helsinki traffic in 2007 was 261 t (H2) a-1. Hydrogen, methane and carbon monoxide are connected with each other through the atmospheric methane oxidation process, in which formaldehyde is produced as an important intermediate. The photochemical degradation of formaldehyde produces hydrogen and carbon monoxide as end products. Examination of back-trajectories revealed long-range transportation of carbon monoxide and methane. The trajectories can be grouped by applying cluster and source analysis methods. Thus natural and anthropogenic emission sources can be separated by analyzing trajectory clusters.

Seismic Tomography and Earthquake Mechanism Beneath the Central Fennoscandian Shield

The aim of this thesis was to study the seismic tomography structure of the earth s crust together with earthquake distribution and mechanism beneath the central Fennoscandian Shield, mainly in southern and central Finland. The earthquake foci and some fault plane solutions are correlated with 3-D images of the velocity tomography. The results are discussed in relation to the stress field of the Shield and with other geophysical, e.g. geomagnetic, gravimetric, tectonic, and anisotropy studies of the Shield. The earthquake data of the Fennoscandian Shield has been extracted from the Nordic earthquake parameter data base which was founded at the time of inception of the earthquake catalogue for northern Europe. Eight earlier earthquake source mechanisms are included in a pilot study on creating a novel technique for calculating an earthquake fault plane solution. Altogether, eleven source mechanisms of shallow, weak earthquakes are related in the 3-D tomography model to trace stresses of the crust in southern and central Finland. The earthquakes in the eastern part of the Fennoscandian Shield represent low-active, intraplate seismicity. Earthquake mechanisms with NW-SE oriented horizontal compression confirm that the dominant stress field originates from the ridge-push force in the North Atlantic Ocean. Earthquakes accumulate in coastal areas, in intersections of tectonic lineaments, in main fault zones or are bordered by fault lines. The majority of Fennoscandian earthquakes concentrate on the south-western Shield in southern Norway and Sweden. Onwards, epicentres spread via the ridge of the Shield along the west-coast of the Gulf of Bothnia northwards along the Tornio River - Finnmark fault system to the Barents Sea, and branch out north-eastwards via the Kuusamo region to the White Sea Kola Peninsula faults. The local seismic tomographic method was applied to find the terrane distribution within the central parts of the Shield the Svecofennian Orogen. From 300 local explosions a total of 19765 crustal Pg- and Sg-wave arrival times were inverted to create independent 3-D Vp and Vs tomographic models, from which the Vp/Vs ratio was calculated. The 3-D structure of the crust is presented as a P-wave and for the first time as an S-wave velocity model, and also as a Vp/Vs-ratio model of the SVEKALAPKO area that covers 700x800 km2 in southern and central Finland. Also, some P-wave Moho-reflection data was interpolated to image the relief of the crust-mantle boundary (i.e. Moho). In the tomography model, the seismic velocities vary smoothly. The lateral variations are larger for Vp (dVp =0.7 km/s) than for Vs (dVs =0.4 km/s). The Vp/Vs ratio varies spatially more distinctly than P- and S-wave velocities, usually from 1.70 to 1.74 in the upper crust and from 1.72 to 1.78 in the lower crust. Schist belts and their continuations at depth are associated with lower velocities and lower Vp/Vs ratios than in the granitoid areas. The tomography modelling suggests that the Svecofennian Orogen was accreted from crustal blocks ranging in size from 100x100 km2 to 200x200 km2 in cross-sectional area. The intervening sedimentary belts have ca. 0.2 km/s lower P- and S-wave velocities and ca. 0.04 lower Vp/Vs ratios. Thus, the tomographic model supports the concept that the thick Svecofennian crust was accreted from several crustal terranes, some hidden, and that the crust was later modified by intra- and underplating. In conclusion, as a novel approach the earthquake focal mechanism and focal depth distribution is discussed in relation to the 3-D tomography model. The schist belts and the transformation zones between the high- and low-velocity anomaly blocks are characterized by deeper earthquakes than the granitoid areas where shallow events dominate. Although only a few focal mechanisms were solved for southern Finland, there is a trend towards strike-slip and oblique strike-slip movements inside schist areas. The normal dip-slip type earthquakes are typical in the seismically active Kuusamo district in the NE edge of the SVEKALAPKO area, where the Archean crust is ca. 15-20 km thinner than the Proterozoic Svecofennian crust. Two near vertical dip-slip mechanism earthquakes occurred in the NE-SW junction between the Central Finland Granitoid Complex and the Vyborg rapakivi batholith, where high Vp/Vs-ratio deep-set intrusion splits the southern Finland schist belt into two parts in the tomography model.