Signal/Image Processing

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour-based invariants in the presence of large illumination changes between training and test data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) we employ a more sophisticated photometric model of the camera and show how its parameters can be estimated, (ii) we derive several novel colour-based face invariants, and (iii) on a large database of video sequences we examine and evaluate the largest number of colour-based representations in the literature. Our results suggest that colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

AIRCC's International Journal on Cybernetics & Informatics (IJCI) is an open access-Computer Science Conference Proceedings series that welcomes nonprofit conferences* to publish their proceedings / post conference proceedings. This series intends to focus on publishing high quality papers to help the scientific community furthering our goal to preserve and disseminate scientific knowledge. Conference proceedings are accepted for publication in International Journal on Cybernetics & Informatics (IJCI) based on peer-reviewed full papers and revised short papers that target international scientific community and latest Computer Science and Information Technology trends. Our mission is to provide the most valuable publication service.

* Nonprofit conferences - Conferences conducted by Educational Institutions with low registration fee (minimal charges).

AC (Alternating Current) – Elecktrokinetics is a group of phenomena that can be used to manipulate particles and fluids in rapid and versatile ways. It is quickly becoming the center of the many biomedical chip applications [1]. These chips can be used in numerous applications such as health and food science. This project used AC – Elecktrokinetics phenomenon called DEP (Dielectrophoresis) to investigate the life cells. To elaborate, the main part of the project acquires to develop a circuitry device that was connected to an usb oscilloscope that was used for amplification among other functions. Then execute successfully dielectrophoresis on yeast cells and measure their impedances. After the electrical properties (the functions of the complex cells’ structure that can be measured electronically) such as impedances and permittivity of the cells can be observed, then the cells can be manipulated among other things that can be done on the cells by using techniques such as Electrical Impedance Spectroscopy (EIS). Furthermore, this project examined electrical characterizations of cells by applying two signals on the cells instead
of one (which was done in a previous similar project).

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we propose a novel, general recognition framework for efficient matching of individual face images, sets or sequences. The framework is based on simple image processing filters that compete with unprocessed greyscale input to yield a single matching score between individuals. It is shown how the discrepancy between illumination conditions between novel input and the training data set can be estimated and used to weigh the contribution of two competing representations. We describe an extensive empirical evaluation of the proposed method on 171 individuals and over 1300 video sequences with extreme illumination, pose and head motion variation. On this challenging data set our algorithm consistently demonstrated a dramatic performance improvement over traditional filtering approaches. We demonstrate a reduction of 50-75% in recognition error rates, the best performing method-filter combination correctly recognizing 96% of the individuals.

Opportunities for the use of noninvasive tomographic sensor technology are described and reviewed critically. Imaging instruments based on electrical sensing methods are discussed with respect to a number of process applications, including measurement of component concentration profiles, phase boundaries, component velocities and component mass flow rate. The use of low-noise electronic devices for process image sensing and the computationally intensive digital signal processing systems for image reconstruction are discussed. Limitations of current electronic techniques, particularly for future ultra high speed image reconstruction are revealed and directions for future progress are elucidated.

Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.

AIRCC's International Journal on Cybernetics & Informatics (IJCI) is an open access-Computer Science Conference Proceedings series that welcomes nonprofit conferences* to publish their proceedings / post conference proceedings. This series intends to focus on publishing high quality papers to help the scientific community furthering our goal to preserve and disseminate scientific knowledge. Conference proceedings are accepted for publication in International Journal on Cybernetics & Informatics (IJCI) based on peer-reviewed full papers and revised short papers that target international scientific community and latest Computer Science and Information Technology trends. Our mission is to provide the most valuable publication service.

Achieving illumination invariance in the presence of large pose changes remains one of the most challenging aspects of automatic face recognition from low resolution imagery. In this paper, we propose a novel recognition methodology for their robust and efficient matching. The framework is based on outputs of simple image processing filters that compete with unprocessed greyscale input to yield a single matching score between two individuals. Specifically, we show how the discrepancy of the illumination conditions between query input and training (gallery) data set can be estimated implicitly and used to weight the contributions of the two competing representations. The weighting parameters are representation-specific (i.e. filter-specific), but not gallery-specific. Thus, the computationally demanding, learning stage of our algorithm is offline-based and needs to be performed only once, making the added online overhead minimal. Finally, we describe an extensive empirical evaluation of the proposed method in both a video and still image-based setup performed on five databases, totalling 333 individuals, over 1660 video sequences and 650 still images, containing extreme variation in illumination, pose and head motion. On this challenging data set our algorithm consistently demonstrated a dramatic performance improvement over traditional filtering approaches. We demonstrate a reduction of 50–75% in recognition error rates, the best performing method-filter combination correctly recognizing 97% of the individuals.

Abstract Rhythms in the gamma range and the beta range are associated with attention, perception, and cognition. Therefore, the mechanism of how long-distance synchrony between participating sites is achieved becomes one of the important issues of ...

In this paper a modular approach of gradual confidence for facial feature extraction over real video frames is presented. The problem is being dealt under general imaging conditions and soft presumptions. The proposed methodology copes with large variations in the appearance of diverse subjects, as well as of the same subject in various instances within real video sequences. Areas of the face that statistically seem to be outstanding form an initial set of regions that are likely to include information about the features of interest. Enhancement of these regions produces closed objects, which reveal-through the use of a fuzzy system-a dominant angle, i.e. the facial rotation angle. The object set is restricted using the dominant angle. An exhaustive search is performed among all candidate objects, matching a pattern that models the relative position of the eyes and the mouth. Labeling of the winner features can be used to evaluate the features extracted and provide feedback in an iterative framework. A subset of the MPEG-4 facial definition or facial animation parameter set can be obtained. This gradual feature revelation is performed under optimization for each step, producing a posteriori knowledge about the face and leading to a step-by-step visualization of the features in search.

org/sipo/index Scope 6 th International Conference on Signal, Image Processing (SIPO 2022) is a forum for presenting new advances and research results in the fields of Signal and Image Processing. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences.

1. lntroduction We recently presented an application of twodimensional (2D) wavelet transform (WT) to hologram analysis.l Our purpose was to determine the three-dimensional trajectories of glass fibers drawn out in a turbulent flame, and high-speed in-line holography was used to visualize the sample volume.2 However, the strong local variations of the refractive index hindered the use of the holographic images. We demonstrated that the reliability of the reconstruction step could be improved by means of a digital method. In our approach the diffraction patterns of glass fibers recorded on the holographic plate were directly scanned by a CCD camera and analyzedby a wavelet-based method. We determined the axial location z andorientation 0 of a fiber element by searching for the values of these two parameters (i.e., scaling factor o and angular orientation 0), which led to the maximum of the WT modulus. The computation of successive correlations between the daughter wavelets and the diffraction pattern were carried out for 20 vaLues of angle 0 and for 30 values of the scaling The authors are with Unité Mixte de Recherche 6614-CORIA, High-speed in-line holography is used to visualize the trajectories of glass fibers being drawn out in a turbulent flame. To improve the signal-to-noise ratio, the images are not observed by a conventional reconstruction setup, but the holographic plate is placed directly on the input plane of a wavelettransform optical system. This processing system is based on a Vanderlugt correlator with inclusion of

Using a new multi-wavelength technique applied on the solar corona SOHO/EIT images containing magnetoacoustic waves (EIT waves), we constrain the wave phase velocity and, as well, some β-model, height related considerations for the vertical extent of the wave, applied on the particular EIT wave triggered by the eruptive event from 15th of August, 2001.

A growing trend has been observed in recent research in wireless communication systems. However, several limitations still exist, such as packet loss, limited bandwidth and inefficient use of available bandwidth that needs further investigation and research. In light of the above limitations, this paper uses adaptive modulation under various parameters, such as signal to interference plus noise ratio (SINR), and communication channel’s distances. The primary goal is to minimize bit error rate (BER), improve throughput and utilize the available bandwidth efficiently. Additionally, the impact of Additive White Gaussian Noise (AWGN), Rayleigh and Rician fading channels on the performance of various modulation schemes are also studied. The simulation results demonstrate that our proposed technique optimally improves the BER and spectral efficiency in the long-range communication as compared to the fixed modulation schemes under the co-channel interference of surrounding base stations. T...

Most image processing applications require noise elimination. For example, in applications where derivative operators are applied, any noise in the image can result in serious errors. Impulsive noise appears as a sprinkle of dark and bright spots. Transmission errors, ...

6th International Conference on Computer Science, Engineering and Information Technology (CSEIT-2019)
November 23 ~ 24, 2019, Zurich, Switzerland
Volume Editors : Natarajan Meghanathan Dhinaharan Nagamalai (Eds)
ISBN: 978-1-925953-09-1
Volume 9, Number 13, November 2019
http://airccse.org/csit/V9N13.html