Palmprint Recognition Based on Subspace Analysis of Gabor Filter Bank

This paper introduces a new technique for palmprint recognition based on Fisher Linear Discriminant Analysis (FLDA) and Gabor filter bank. This method involves convolving a palmprint image with a bank of Gabor filters at different scales and rotations for robust palmprint features extraction. Once these features are extracted, FLDA is applied for dimensionality reduction and class separability. Since the palmprint features are derived from the principal lines, wrinkles and texture along the palm area. One should carefully consider this fact when selecting the appropriate palm region for the feature extraction process in order to enhance recognition accuracy. To address this problem, an improved region of interest (ROI) extraction algorithm is introduced. This algorithm allows for an efficient extraction of the whole palm area by ignoring all the undesirable parts, such as the fingers and background. Experiments have shown that the proposed method yields attractive performances as evidenced by an Equal Error Rate (EER) of 0.03%.

Playful structure: a novel image of early years pedagogy for primary school classrooms

Playful structure is a new pedagogic image representing a more balanced and integrated perspective on early years pedagogy, aiming to blend apparent dichotomies and contradictions and to sustain and evolve play-based practice beyond Year 1. Playful structure invites teachers and children to initiate and maintain a degree of playfulness in the child’s whole learning experience, even when the learning intentions demand a supportive structure. Thus, playfulness becomes characteristic of the interaction between adult and the child and not just characteristic of child-initiated versus adult-initiated activities, or of play-time versus task-time. The paper is based on intensive observations and interviews with teachers in Northern Ireland who participated in a play-based and informal curriculum. This paper explains how playful structure rests on complementary processes of infusion of structure into play-based activities and infusion of playfulness into more structured activities, illustrated by cameos. ‘Infusion’ suggests the subtle blending process that allows apparent dichotomies and contradictions to be resolved in practice.

Hybrid image/ray-shooting UHF radio propagation predictor for populated indoor environments

A novel model for indoor wireless communication, based on a dual image and ray-shooting approach, is presented. The model, capable of improved site-specific indoor propagation prediction, considers multiple human bodies moving within the environment. In a modern office at 2.45GHz, the combined effect of pedestrian traffic and a moving receiver causes rapid temporal fading of up to 30dB.

Rao-Blackwellised particle filter for colour-based tracking

Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved

An efficient particle filter for color-based tracking in complex scenes

In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

Automatic FPGA Synthesis of Memory Intensive C-based Kernels

Realising high performance image and signal processing
applications on modern FPGA presents a challenging implementation problem due to the large data frames streaming through these systems. Specifically, to meet the high bandwidth and data storage demands of these applications, complex hierarchical memory architectures must be manually specified
at the Register Transfer Level (RTL). Automated approaches which convert high-level operation descriptions, for instance in the form of C programs, to an FPGA architecture, are unable to automatically realise such architectures. This paper
presents a solution to this problem. It presents a compiler to automatically derive such memory architectures from a C program. By transforming the input C program to a unique dataflow modelling dialect, known as Valved Dataflow (VDF), a mapping and synthesis approach developed for this dialect can
be exploited to automatically create high performance image and video processing architectures. Memory intensive C kernels for Motion Estimation (CIF Frames at 30 fps), Matrix Multiplication (128x128 @ 500 iter/sec) and Sobel Edge Detection (720p @ 30 fps), which are unrealisable by current state-of-the-art C-based synthesis tools, are automatically derived from a C description of the algorithm.

Detection of Paralytic Shellfish Toxins by a Solid-Phase Inhibition Immunoassay Using a Microsphere-Flow Cytometry System

Paralytic shellfish poisoning is a toxic syndrome described in humans following the ingestion of seafood contaminated with saxitoxin and/or its derivatives. The presence of these toxins in shellfish is considered an important health threat and their levels in seafood destined to human consumption are regulated in many countries, as well as the levels of other chemically unrelated toxins. We studied the feasibility of immunodetection of saxitoxin and its analogs using a solid-phase microsphere assay coupled to flow cytometry detection in a Luminex 200 system. The technique consists of a competition assay where the toxins in solution compete with bead-bound saxitoxin for binding to an antigonyautoxin 2/3 monoclonal antibody (GT-13A). The assay allowed the detection of saxitoxin both in buffer and mussel extracts in the range of 2.2-19.7 ng/mL (IC(20)-IC(80)). Moreover, the assay cross-reactivity with other toxins of the group is similar to previously published immunoassays, with adequate detection of most analogs except N-1 hydroxy analogs. The recovery rate of the assay for saxitoxin was close to 100%. This microsphere-based immunoassay is suitable to be used as a screening method, detecting saxitoxin from 260 to 2360 µg/kg. This microsphere/flow cytometry system provided similar sensitivities to previously published immunoassays and provides a solid background for the development of easy, flexible multiplexing of toxin detection in one sample.

VLSI architectures for digital image coding

A number of high-performance VLSI architectures for real-time image coding applications are described. In particular, attention is focused on circuits for computing the 2-D DCT (discrete cosine transform) and for 2-D vector quantization. The former circuits are based on Winograd algorithms and comprise a number of bit-level systolic arrays with a bit-serial, word-parallel input. The latter circuits exhibit a similar data organization and consist of a number of inner product array circuits. Both circuits are highly regular and allow extremely high data rates to be achieved through extensive use of parallelism.

Programmable image processing chip

A new high performance, programmable image processing chip targeted at video and HDTV applications is described. This was initially developed for image small object recognition but has much broader functional application including 1D and 2D FIR filtering as well as neural network computation. The core of the circuit is made up of an array of twenty one multiplication-accumulation cells based on systolic architecture. Devices can be cascaded to increase the order of the filter both vertically and horizontally. The chip has been fabricated in a 0.6 µ, low power CMOS technology and operates on 10 bit input data at over 54 Megasamples per second. The introduction gives some background to the chip design and highlights that there are few other comparable devices. Section 2 gives a brief introduction to small object detection. The chip architecture and the chip design will be described in detail in the later sections.

Real-time GPU color-based segmentation of football players

In this paper, we propose a multi-camera application capable of processing high resolution images and extracting features based on colors patterns over graphic processing units (GPU). The goal is to work in real time under the uncontrolled environment of a sport event like a football match. Since football players are composed for diverse and complex color patterns, a Gaussian Mixture Models (GMM) is applied as segmentation paradigm, in order to analyze sport live images and video. Optimization techniques have also been applied over the C++ implementation using profiling tools focused on high performance. Time consuming tasks were implemented over NVIDIA's CUDA platform, and later restructured and enhanced, speeding up the whole process significantly. Our resulting code is around 4-11 times faster on a low cost GPU than a highly optimized C++ version on a central processing unit (CPU) over the same data. Real time has been obtained processing until 64 frames per second. An important conclusion derived from our study is the scalability of the application to the number of cores on the GPU. © 2011 Springer-Verlag.

Optimization of image quality and dose for Varian aS500 electronic portal imaging devices (EPIDs)

This study was carried out to investigate whether the electronic portal imaging (EPI) acquisition process could be optimized, and as a result tolerance and action levels be set for the PIPSPro QC-3V phantom image quality assessment. The aim of the optimization process was to reduce the dose delivered to the patient while maintaining a clinically acceptable image quality. This is of interest when images are acquired in addition to the planned patient treatment, rather than images being acquired using the treatment field during a patient's treatment. A series of phantoms were used to assess image quality for different acquisition settings relative to the baseline values obtained following acceptance testing. Eight Varian aS500 EPID systems on four matched Varian 600C/D linacs and four matched Varian 2100C/D linacs were compared for consistency of performance and images were acquired at the four main orthogonal gantry angles. Images were acquired using a 6 MV beam operating at 100 MU min(-1) and the low-dose acquisition mode. Doses used in the comparison were measured using a Farmer ionization chamber placed at d(max) in solid water. The results demonstrated that the number of reset frames did not have any influence on the image contrast, but the number of frame averages did. The expected increase in noise with corresponding decrease in contrast was also observed when reducing the number of frame averages. The optimal settings for the low-dose acquisition mode with respect to image quality and dose were found to be one reset frame and three frame averages. All patients at the Northern Ireland Cancer Centre are now imaged using one reset frame and three frame averages in the 6 MV 100 MU min(-1) low-dose acquisition mode. Routine EPID QC contrast tolerance (+/-10) and action (+/-20) levels using the PIPSPro phantom based around expected values of 190 (Varian 600C/D) and 225 (Varian 2100C/D) have been introduced. The dose at dmax from electronic portal imaging has been reduced by approximately 28%, and while the image quality has been reduced, the images produced are still clinically acceptable.

Multi-detection of Paralytic, Diarrheic and Amnesic Shellfish Toxins by an Inhibition Immunoassay Using a Microsphere-Flow Cytometry System

The presence of paralytic shellfish poisoning (PSP), diarrheic shellfish poisoning (DSP) and amnesic shellfish poisoning (ASP) toxins in seafood is a severe and growing threat to human health. In order to minimize the risks of human exposure, the maximum content of these toxins in seafood has been limited by legal regulations worldwide. The regulated limits are established in equivalents of the main representatives of the groups: saxitoxin (STX), okadaic acid (OA) and domoic acid (DA), for PSP, DSP and ASP, respectively. In this study a multi-detection method to screen shellfish samples for the presence of these toxins simultaneously was developed. Multiplexing was achieved using a solid-phase microsphere assay coupled to flow-fluorimetry detection, based on the Luminex xMap technology. The multi-detection method consists of three simultaneous competition immunoassays. Free toxins in solution compete with STX, OA or DA immobilized on the surface of three different classes of microspheres for binding to specific monoclonal antibodies. The IC50 obtained in buffer was similar in single- and multi-detection: 5.6 ± 1.1 ng/mL for STX, 1.1 ± 0.03 ng/mL for OA and 1.9 ± 0.1 ng/mL for DA. The sample preparation protocol was optimized for the simultaneous extraction of STX, OA and DA with a mixture of methanol and acetate buffer. The three immunoassays performed well with mussel and scallop matrixes displaying adequate dynamic ranges and recovery rates (around 90 % for STX, 80 % for OA and 100 % for DA). This microsphere-based multi-detection immunoassay provides an easy and rapid screening method capable of detecting simultaneously in the same sample three regulated groups of marine toxins.

Using entropy based mean shift filter and modified watershed transform for grain segmentation

Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper,we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice.However,due to the over-segmentation issue,this technique has experienced poor performance in various applications,such as inhomogeneous background and connected targets. To solve this problem,we present a combination of two classical techniques to handle this issue.In the first step,a mean shift filter is used to eliminate the inhomogeneous background, where entropy is used to be a converging criterion. Secondly,a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.

Logic and Memory Design Based on Unequal Error Protection for Voltage-scalable, Robust and Adaptive DSP Systems

In this paper, we propose a system level design approach considering voltage over-scaling (VOS) that achieves error resiliency using unequal error protection of different computation elements, while incurring minor quality degradation. Depending on user specifications and severity of process variations/channel noise, the degree of VOS in each block of the system is adaptively tuned to ensure minimum system power while providing "just-the-right" amount of quality and robustness. This is achieved, by taking into consideration block level interactions and ensuring that under any change of operating conditions, only the "less-crucial" computations, that contribute less to block/system output quality, are affected. The proposed approach applies unequal error protection to various blocks of a system-logic and memory-and spans multiple layers of design hierarchy-algorithm, architecture and circuit. The design methodology when applied to a multimedia subsystem shows large power benefits ( up to 69% improvement in power consumption) at reasonable image quality while tolerating errors introduced due to VOS, process variations, and channel noise.