Search results for: Image signal processor

Authors: M. Sadeghi, A.H. Jafari, S.M.P. Firoozabadi

Abstract:

Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.

Keywords: Chaos, Deep Brain Stimulation, Parkinson's Disease, Stimulation Parameters, tremor.

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Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst

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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.

Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Manually annotating pathway diagrams is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: Biological pathway, gene identification, object detection, Siamese network, ResNet.

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Authors: J. Hassan

Abstract:

Water 2H NMR signal on the surface of nano-silica material, MCM-41, consists of two overlapping resonances. The 2H water spectrum shows a superposition of a Lorentzian line shape and the familiar NMR powder pattern line shape, indicating the existence of two spin components. Chemical exchange occurs between these two groups. Decomposition of the two signals is a crucial starting point for study the exchange process. In this article we have determined these spin component populations along with other important parameters for the 2H water NMR signal over a temperature range between 223 K and 343 K.

Keywords: Nano-Silica, surface water, NMR

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Authors: Aaron J. Small, Craig A. Fletcher

Abstract:

This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Keywords: Rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design.

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Authors: Jong-Bae Lee, Seongsoo Lee

Abstract:

Local interconnect network (LIN) is a communication protocol that combines sensors, actuators, and processors to a functional module in automotive applications. In this paper, a LIN ver. 2.2A controller was designed in Verilog hardware description language (Verilog HDL) and implemented in field-programmable gate array (FPGA). Its operation was verified by making full-scale LIN network with the presented FPGA-implemented LIN controller, commercial LIN transceivers, and commercial processors. When described in Verilog HDL and synthesized in 0.18 μm technology, its gate size was about 2,300 gates.

Keywords: Local interconnect network, controller, transceiver, processor.

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Authors: Baisa L. Gunjal, Suresh N. Mali

Abstract:

Medical images require special safety and confidentiality because critical judgment is done on the information provided by medical images. Transmission of medical image via internet or mobile phones demands strong security and copyright protection in telemedicine applications. Here, highly secured and robust watermarking technique is proposed for transmission of image data via internet and mobile phones. The Region of Interest (ROI) and Non Region of Interest (RONI) of medical image are separated. Only RONI is used for watermark embedding. This technique results in exact recovery of watermark with standard medical database images of size 512x512, giving 'correlation factor' equals to 1. The correlation factor for different attacks like noise addition, filtering, rotation and compression ranges from 0.90 to 0.95. The PSNR with weighting factor 0.02 is up to 48.53 dBs. The presented scheme is non blind and embeds hospital logo of 64x64 size.

Keywords: Compression, DWT, ROI, Scrambling, Vertices

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Authors: J.Dinesh Peter

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This paper describes a new method for affine parameter estimation between image sequences. Usually, the parameter estimation techniques can be done by least squares in a quadratic way. However, this technique can be sensitive to the presence of outliers. Therefore, parameter estimation techniques for various image processing applications are robust enough to withstand the influence of outliers. Progressively, some robust estimation functions demanding non-quadratic and perhaps non-convex potentials adopted from statistics literature have been used for solving these. Addressing the optimization of the error function in a factual framework for finding a global optimal solution, the minimization can begin with the convex estimator at the coarser level and gradually introduce nonconvexity i.e., from soft to hard redescending non-convex estimators when the iteration reaches finer level of multiresolution pyramid. Comparison has been made to find the performance of the results of proposed method with the results found individually using two different estimators.

Keywords: Image Processing, Affine parameter estimation, Outliers, Robust Statistics, Robust M-estimators

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Authors: S. Divya Gnanarathinam, S. Sundaramurthy

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The tremendous increase in the population of the world creates the immediate need for the energy resources. All the people in the world need the sustainable energy resources which have low costs. Solar energy is appraised as one of the main energy resources in warm countries. The areas in the west of India like Rajasthan, Gujarat, etc. are immensely rich in solar energy resources. This paper deals with the development of dual axis solar tracker using Arduino board. Depending on the astronomical estimates of the sun from the GPS and sensor image processing outcomes, a methodology is proposed to locate the position of the sun to obtain the maximum solar energy. Based on the outcomes, the solar tracking system figures out whether to use image processing outcomes or astronomical estimates to attain the maximum efficiency of the solar panel. Finally, the experimental values obtained from the solar tracker for both the sunny and the rainy days are being tabulated.

Keywords: Dual axis solar tracker, Arduino board, LDR sensors, global positioning system.

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Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: Anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, Split Bregman Algorithm.

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Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

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Mostly the systems are dealing with time varying signals. The Power efficiency can be achieved by adapting the system activity according to the input signal variations. In this context an adaptive rate filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by following the input signal local variations. Thus, it correlates the processing activity with the signal variations. Interpolation is required in the proposed technique. A drastic reduction in the interpolation error is achieved by employing the symmetry during the interpolation process. Processing error of the proposed technique is calculated. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. Results promise a significant gain of the computational efficiency and hence of the power consumption.

Keywords: Level Crossing Sampling, Activity Selection, Rate Filtering, Computational Complexity, Interpolation Error.

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Authors: Normi Abdul Hadi, Arsmah Ibrahim, Fatimah Yahya, Jamaludin Md. Ali

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Beta-spline is built on G2 continuity which guarantees smoothness of generated curves and surfaces using it. This curve is preferred to be used in object design rather than reconstruction. This study however, employs the Beta-spline in reconstructing a 3- dimensional G2 image of the Stanford Rabbit. The original data consists of multi-slice binary images of the rabbit. The result is then compared with related works using other techniques.

Keywords: Beta-spline, multi-slice image, rectangular surface, 3D reconstruction

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram (PCG) signals can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded PCG signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded Electrocardiograms (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show on average a segmentation testing performance average of 76% sensitivity and 94% specificity.

Keywords: Heart sounds, PCG segmentation, event detection, Recurrent Neural Networks, PCG curve length.

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Authors: Mazhar B. Tayel, Eslam I. AlSaba

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Heart is the most important part in the body of living organisms. It affects and is affected by any factor in the body. Therefore, it is a good detector for all conditions in the body. Heart signal is a non-stationary signal; thus, it is utmost important to study the variability of heart signal. The Heart Rate Variability (HRV) has attracted considerable attention in psychology, medicine and has become important dependent measure in psychophysiology and behavioral medicine. The standards of measurements, physiological interpretation and clinical use for HRV that are most often used were described in many researcher papers, however, remain complex issues are fraught with pitfalls. This paper presents one of the nonlinear techniques to analyze HRV. It discusses many points like, what Poincaré plot is and how Poincaré plot works; also, Poincaré plot's merits especially in HRV. Besides, it discusses the limitation of Poincaré cause of standard deviation SD1, SD2 and how to overcome this limitation by using complex correlation measure (CCM). The CCM is most sensitive to changes in temporal structure of the Poincaré plot as compared toSD1 and SD2.

Keywords: Heart rate variability, chaotic system, Poincaré, variance, standard deviation, complex correlation measure.

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Authors: Yiannis G. Smirlis

Abstract:

The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: Data envelopment analysis, interval DEA, efficiency classification, efficiency prediction.

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Authors: B. Bagheri Nakhjavanlo, T. S. Ellis, P.Raoofi, Sh.ziari

Abstract:

This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the level set formulation aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets, and are shown to be more effective than other approaches in coping with intensity inhomogeneities. We have applied the Courant Friedrichs Levy (CFL) condition as stability criterion for our algorithm.

Keywords: Image segmentation, Level-sets, Local fitting binary, Thoracic aorta.

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Authors: Mario Mastriani, Alberto E. Giraldez

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In this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman-s filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman-s filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test synthetic aperture radar (SAR) images.

Keywords: Kalman's filter, shrinkage, speckle, wavelets.

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Authors: Dalvinder Singh Dhaliwal, Parvinder S. Sandhu, S. N. Panda

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This paper is on the general discussion of memory consistency model like Strict Consistency, Sequential Consistency, Processor Consistency, Weak Consistency etc. Then the techniques for implementing distributed shared memory Systems and Synchronization Primitives in Software Distributed Shared Memory Systems are discussed. The analysis involves the performance measurement of the protocol concerned that is Multiple Writer Protocol. Each protocol has pros and cons. So, the problems that are associated with each protocol is discussed and other related things are explored.

Keywords: Distributed System, Single owner protocol, Multiple owner protocol

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Authors: Guo Xiuhua, Sun Tao, Wu Haifeng, He Wen, Liang Zhigang, Zhang Mengxia, Guo Aimin, Wang Wei

Abstract:

Purpose: To explore the use of Curvelet transform to extract texture features of pulmonary nodules in CT image and support vector machine to establish prediction model of small solitary pulmonary nodules in order to promote the ratio of detection and diagnosis of early-stage lung cancer. Methods: 2461 benign or malignant small solitary pulmonary nodules in CT image from 129 patients were collected. Fourteen Curvelet transform textural features were as parameters to establish support vector machine prediction model. Results: Compared with other methods, using 252 texture features as parameters to establish prediction model is more proper. And the classification consistency, sensitivity and specificity for the model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based on texture features extracted from Curvelet transform, support vector machine prediction model is sensitive to lung cancer, which can promote the rate of diagnosis for early-stage lung cancer to some extent.

Keywords: CT image, Curvelet transform, Small pulmonary nodules, Support vector machines, Texture extraction.

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Authors: Kamran Hameed, Adeel Mumtaz, S.A.M. Gilani

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In this paper, we start by first characterizing the most important and distinguishing features of wavelet-based watermarking schemes. We studied the overwhelming amount of algorithms proposed in the literature. Application scenario, copyright protection is considered and building on the experience that was gained, implemented two distinguishing watermarking schemes. Detailed comparison and obtained results are presented and discussed. We concluded that Joo-s [1] technique is more robust for standard noise attacks than Dote-s [2] technique.

Keywords: Digital image, Copyright protection, Watermarking, Wavelet transform.

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Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara

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The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.

Keywords: Spacecraft control, quantized control, nonlinear control, random dither method.

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Authors: Zhenyu Zhang, Qingbin Gao

Abstract:

Low-resolution digital encoder (LRDE) is commonly adopted as a position sensor in low-cost and resource-constraint applications. Traditionally, a digital encoder is modeled as a quantizer without considering the initial position of the LRDE. However, it cannot be applied to extreme LRDE for which stroke of angular motion is only a few times of resolution of the encoder. Besides, the actual angular motion is substantially distorted by this extreme LRDE so that the encoder reading does not faithfully represent the actual angular motion. This paper presents a modeling method for extreme LRDE by taking into account the initial position of the LRDE. For a control system with sinusoidal reference signal and extreme LRDE, this paper analyzes the characteristics of angular motion. Specifically, two descriptors of sinusoidal angular motion are studied, which essentially sheds light on the actual angular motion from extreme LRDE.

Keywords: Low resolution digital encoder, resource-constraint control system, sinusoidal reference signal, servo motion control.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

Abstract:

One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: Wen W. Zhang, Qian Chen

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Electron multiplying charge coupled devices (EMCCDs) have revolutionized the world of low light imaging by introducing on-chip multiplication gain based on the impact ionization effect in the silicon. They combine the sub-electron readout noise with high frame rates. Signal-to-noise Ratio (SNR) is an important performance parameter for low-light-level imaging systems. This work investigates the SNR performance of an EMCCD operated in Non-inverted Mode (NIMO) and Inverted Mode (IMO). The theory of noise characteristics and operation modes is presented. The results show that the SNR of is determined by dark current and clock induced charge at high gain level. The optimum SNR performance is provided by an EMCCD operated in NIMO in short exposure and strong cooling applications. In contrast, an IMO EMCCD is preferable.

Keywords: electron multiplying charge coupled devices, noise characteristics, operation modes, signal-to-noise ratioperformance

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Authors: Carmen Navarrete, Eloy Anguiano

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In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.

Keywords: Dynamic network topology, resource and task allocation, parallel computing, heterogeneous computing, dynamic reconfiguration.

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: Texture classification, texture descriptor, SIFT, SURF, ORB.

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Authors: Sanghoon Kim, Sun-Tae Chung, Souhwan Jung, Dusik Oh, Jaemin Kim, Seongwon Cho

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Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported so far still need to be improved about precision and computational time for successful applications. In this paper, we propose an eye location method based on multi-scale Gabor feature vectors, which is more robust with respect to initial points. The eye localization based on Gabor feature vectors first needs to constructs an Eye Model Bunch for each eye (left or right eye) which consists of n Gabor jets and average eye coordinates of each eyes obtained from n model face images, and then tries to localize eyes in an incoming face image by utilizing the fact that the true eye coordinates is most likely to be very close to the position where the Gabor jet will have the best Gabor jet similarity matching with a Gabor jet in the Eye Model Bunch. Similar ideas have been already proposed in such as EBGM (Elastic Bunch Graph Matching). However, the method used in EBGM is known to be not robust with respect to initial values and may need extensive search range for achieving the required performance, but extensive search ranges will cause much more computational burden. In this paper, we propose a multi-scale approach with a little increased computational burden where one first tries to localize eyes based on Gabor feature vectors in a coarse face image obtained from down sampling of the original face image, and then localize eyes based on Gabor feature vectors in the original resolution face image by using the eye coordinates localized in the coarse scaled image as initial points. Several experiments and comparisons with other eye localization methods reported in the other papers show the efficiency of our proposed method.

Keywords: Eye Localization, Gabor features, Multi-scale, Gabor wavelets.

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Authors: Mohammed A. Al-Manie, Mohammed I. Alkanhal

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In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.

Keywords: Acoustic emissions, acoustic sensors, nondestructivetests, Red Date Palm Weevil, signal processing..

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Authors: Mingxin Zhang, Zhaogan Lu, Junyi Shen

Abstract:

In current common research reports, salient regions are usually defined as those regions that could present the main meaningful or semantic contents. However, there are no uniform saliency metrics that could describe the saliency of implicit image regions. Most common metrics take those regions as salient regions, which have many abrupt changes or some unpredictable characteristics. But, this metric will fail to detect those salient useful regions with flat textures. In fact, according to human semantic perceptions, color and texture distinctions are the main characteristics that could distinct different regions. Thus, we present a novel saliency metric coupled with color and texture features, and its corresponding salient region extraction methods. In order to evaluate the corresponding saliency values of implicit regions in one image, three main colors and multi-resolution Gabor features are respectively used for color and texture features. For each region, its saliency value is actually to evaluate the total sum of its Euclidean distances for other regions in the color and texture spaces. A special synthesized image and several practical images with main salient regions are used to evaluate the performance of the proposed saliency metric and other several common metrics, i.e., scale saliency, wavelet transform modulus maxima point density, and important index based metrics. Experiment results verified that the proposed saliency metric could achieve more robust performance than those common saliency metrics.

Keywords: salient regions, color and texture features, image segmentation, saliency metric

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Authors: Shannon Steinmetz, Ellen Gethner

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In this paper a theoretical foundation is developed to segment, analyze and associate patterns within audio. We explore this on imagery via sonified audio applied to our segmentation framework. The approach involves a geodesic estimator within the statistical manifold, parameterized by musical centricity. We demonstrate viability by processing a database of random imagery to produce statistically significant clusters of similar imagery content.

Keywords: Sonification, musical information geometry, image content extraction, automated quantification, audio segmentation, pattern recognition.

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