Periocular characteristics has gained substantial importance in recent times to supplement the performance of facial biometrics or as a stand-alone characteristics. While most of the current biometric systems for auth...
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ISBN:
(纸本)9780996452700
Periocular characteristics has gained substantial importance in recent times to supplement the performance of facial biometrics or as a stand-alone characteristics. While most of the current biometric systems for authentication or surveillance operate either in NIR spectrum or visible spectrum, the ocular information can be well utilized if a comparison of images from different spectra has to be conducted. In this work, we present a novel approach employing the features obtained from steerable pyramids to compare the ocular images captured from NIR versus the images captured from visible spectrum. The set of features obtained using the proposed cross-spectral approach are then used to learn a multi-class SVM classifier such that the probe image originating from another spectrum can be classified. Further, a fusion frame-work for combining the scores from different orientations of the steerable pyramid is proposed for a particular scale to strengthen the biometric performance of the algorithm. An extensive set of experiments conducted on a large database consisting of ocular images captured from 120 subjects (240 unique ocular instances) indicates the robustness of the proposed approach with a GMR of 100% at the FMR of 0.01% in a benchmark against other state-of-the-art techniques suggesting the applicability of proposed approach to greater extent.
The proceedings contain 41 papers. The special focus in this conference is on imageprocessing and Signal processing. The topics include: A statistical dominance algorithm for edge detection and segmentation of medica...
ISBN:
(纸本)9783319397955
The proceedings contain 41 papers. The special focus in this conference is on imageprocessing and Signal processing. The topics include: A statistical dominance algorithm for edge detection and segmentation of medical images;swarm intelligence approach to 3D medical image segmentation;directional characteristics of mammographic spicules in the complex wavelet domain;discrimination of wheat grain varieties using x-ray images;face localization algorithms as element of silhouette localization process;imaging of the anterior eye segment in the evaluation of corneal dynamics;biopsy needle and tissue deformations detection in elastography supported ultrasound;modification of the ICP algorithm for detection of the occlusal area of dental arches;the fast matching algorithm for rectified stereo images;simple atlas selection strategies for liver segmentation in CT images;automatic 3D segmentation of renal cysts in CT;the importance of the features of the posterior cruciate ligament in diagnosis;multimodal image registration for mandible motion tracking;breast ultrasound tomography;the ultrasound investigation of the medial head of gastrocnemius muscle;the use of doppler effect for tomographic tissue imaging with omnidirectional acoustic data acquisition;analytical statistical approach for fan-beam scanners;3D measurement of geometrical distortion of synchrotron-based perforated polymer with matlab algorithm;improving children diagnostics by efficient multi-label classification method;towards pulse wave velocity estimation using specific ECG and PPG algorithms;averaging of time-warped ECG signals for QT interval measurement and localization of epileptic foci using EEG brain mapping.
This paper represents a literature review of research works concerning the reconstruction of forms of buried objects in an homogeneous soil, applied for the reconstruction of forms of underground cavities. First, we w...
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This book constitutes the refereed proceedings of the 12th IFIP WG 12.5 International conference on Artificial Intelligence Applications and Innovations, AIAI 2016, and three parallel workshops, held in Thessaloniki, ...
ISBN:
(数字)9783319449449
ISBN:
(纸本)9783319449432
This book constitutes the refereed proceedings of the 12th IFIP WG 12.5 International conference on Artificial Intelligence Applications and Innovations, AIAI 2016, and three parallel workshops, held in Thessaloniki, Greece, in September 2016. The workshops are the Third Workshop on New Methods and Tools for Big Data, MT4BD 2016, the 5th Mining Humanistic Data Workshop, MHDW 2016, and the First Workshop on 5G - Putting Intelligence to the Network Edge, 5G-PINE 2016. The 30 revised full papers and 8 short papers presented at the main conference were carefully reviewed and selected from 65 submissions. The 17 revised full papers and 7 short papers presented at the 3 parallel workshops were selected from 33 submissions. The papers cover a broad range of topics such as artificial neural networks, classification, clustering, control systems - robotics, data mining, engineering application of AI, environmental applications of AI, feature reduction, filtering, financial-economics modeling, fuzzy logic, genetic algorithms, hybrid systems, image and video processing, medical AI applications, multi-agent systems, ontology, optimization, pattern recognition, support vector machines, text mining, and Web-social media data AI modeling.
The work is devoted to the synthesis and investigation of parallel algorithm for a finite difference solution of the Poisson equation using the Jacobi method. For example, two-dimensional case demonstrates the efficac...
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The work is devoted to the synthesis and investigation of parallel algorithm for a finite difference solution of the Poisson equation using the Jacobi method. For example, two-dimensional case demonstrates the efficacy of the method of the pyramids in the synthesis of said algorithm.
To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough...
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ISBN:
(数字)9781510603349
ISBN:
(纸本)9781510603332;9781510603349
To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough sets method is proposed for hot slab surface quality assessment. The applicability of the presented method and the devised system are mainly tied to the surface quality inspection for strip, billet and slab surface etcetera. In this work we take into account the complementary advantages in two common machine vision (MV) systems(line array CCD traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging)), and through establishing the model of fuzzy-rough sets in the detection system the seeds for relative fuzzy connectedness(RFC) delineation for ROI can placed adaptively, which introduces the upper and lower approximation sets for RIO definition, and by which the boundary region can be delineated by RFC region competitive classification mechanism. For the first time, a Multi-source CCD imaging based fuzzy-rough sets strategy is attempted for CC-slab surface defects inspection that allows an automatic way of AI algorithms and powerful ROI delineation strategies to be applied to the MV inspection field.
Content based video retrival systems requires video to be segmented into objects. A large number of video segmentation algorithms have been proposed such as semi-automatic and automatic. Semiautomatic methods requires...
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Field programmable gate arrays (FPGAs) are fundamentally different to fixed processors architectures because their memory hierarchies can be tailored to the needs of an algorithm. FPGA compilers for high level languag...
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Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the pro...
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Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting information that have been lost in saturated image areas, in order to enable HDR reconstruction from a single exposure. We show that this problem is well-suited for deep learning algorithms, and propose a deep convolutional neural network (CNN) that is specifically designed taking into account the challenges in predicting HDR values. To train the CNN we gather a large dataset of HDR images, which we augment by simulating sensor saturation for a range of cameras. To further boost robustness, we pre-train the CNN on a simulated HDR dataset created from a subset of the MIT Places database. We demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and low-end cameras that use unknown camera response functions and post-processing. Furthermore, we compare to existing methods for HDR expansion, and show high quality results also for image based lighting. Finally, we evaluate the results in a subjective experiment performed on an HDR display. This shows that the reconstructed HDR images are visually convincing, with large improvements as compared to existing methods.
Discrete Fourier transform (DFT) finds various applications in signal processing, imageprocessing, artificial intelligent, and fuzzy logic etc. DFT is often computed efficiently with Fast Fourier transform (FF1). The...
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Discrete Fourier transform (DFT) finds various applications in signal processing, imageprocessing, artificial intelligent, and fuzzy logic etc. DFT is often computed efficiently with Fast Fourier transform (FF1). The modified split radix FFT (MSRFET.) algorithm implements a length-N=2(m) DFT achieving a reduction of arithmetic complexity compared to split-radix FF1 (SRFFT). In this paper, a simplified algorithm is proposed for the MSRFFT algorithm, reducing the number of real coefficients evaluated from 5/8N - 2 to 15/32N - 2 and the number of groups of decomposition from 4 to 3. A implementation approach is also presented. The approach makes data-path of the MSRFFT regular similar to that of the radix-2 FFT algorithm. The experimental results show that (1) MSRFFT consumes less time on central processing units (CPUs) with sufficient cache than existing algorithms;(2) the proposed implementation method can save execution time on CPUs and general processing units (GPUs).
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