Edges and bars: where do people see features in 1-D images?

There have been two main approaches to feature detection in human and computer vision - based either on the luminance distribution and its spatial derivatives, or on the spatial distribution of local contrast energy. Thus, bars and edges might arise from peaks of luminance and luminance gradient respectively, or bars and edges might be found at peaks of local energy, where local phases are aligned across spatial frequency. This basic issue of definition is important because it guides more detailed models and interpretations of early vision. Which approach better describes the perceived positions of features in images? We used the class of 1-D images defined by Morrone and Burr in which the amplitude spectrum is that of a (partially blurred) square-wave and all Fourier components have a common phase. Observers used a cursor to mark where bars and edges were seen for different test phases (Experiment 1) or judged the spatial alignment of contours that had different phases (e.g. 0 degrees and 45 degrees ; Experiment 2). The feature positions defined by both tasks shifted systematically to the left or right according to the sign of the phase offset, increasing with the degree of blur. These shifts were well predicted by the location of luminance peaks (bars) and gradient peaks (edges), but not by energy peaks which (by design) predicted no shift at all. These results encourage models based on a Gaussian-derivative framework, but do not support the idea that human vision uses points of phase alignment to find local, first-order features. Nevertheless, we argue that both approaches are presently incomplete and a better understanding of early vision may combine insights from both. (C)2004 Elsevier Ltd. All rights reserved.

A high-power-factor, three-phase isolated AC-DC converter using high-frequency current injection

A single-stage, three-phase AC-to-DC converter topology is proposed for high-frequency power supply applications. The principal features of the circuit include continuous current operation of the three AC input inductors, inherent shaping of the input currents, resulting in high power factor, a transformer isolated output, and only two active devices are required, both soft-switched. Resonant conversion techniques are used, and a high power factor is achieved by injecting high-frequency currents into the three-phase rectifier, producing a high frequency modulation of the rectifier input voltages. The current injection principle is explained and the system operation is confirmed by a combination of simulation and experimental results.

Multi-frequency segmental bio-impedance device:design, development and applications

Bio-impedance analysis (BIA) provides a rapid, non-invasive technique for body composition estimation. BIA offers a convenient alternative to standard techniques such as MRI, CT scan or DEXA scan for selected types of body composition analysis. The accuracy of BIA is limited because it is an indirect method of composition analysis. It relies on linear relationships between measured impedance and morphological parameters such as height and weight to derive estimates. To overcome these underlying limitations of BIA, a multi-frequency segmental bio-impedance device was constructed through a series of iterative enhancements and improvements of existing BIA instrumentation. Key features of the design included an easy to construct current-source and compact PCB design. The final device was trialled with 22 human volunteers and measured impedance was compared against body composition estimates obtained by DEXA scan. This enabled the development of newer techniques to make BIA predictions. To add a ‘visual aspect’ to BIA, volunteers were scanned in 3D using an inexpensive scattered light gadget (Xbox Kinect controller) and 3D volumes of their limbs were compared with BIA measurements to further improve BIA predictions. A three-stage digital filtering scheme was also implemented to enable extraction of heart-rate data from recorded bio-electrical signals. Additionally modifications have been introduced to measure change in bio-impedance with motion, this could be adapted to further improve accuracy and veracity for limb composition analysis. The findings in this thesis aim to give new direction to the prediction of body composition using BIA. The design development and refinement applied to BIA in this research programme suggest new opportunities to enhance the accuracy and clinical utility of BIA for the prediction of body composition analysis. In particular, the use of bio-impedance to predict limb volumes which would provide an additional metric for body composition measurement and help distinguish between fat and muscle content.

Prevalence and audiological features in carriers of GJB2 mutations, c.35delG and c.101T>C (p.M34T), in a UK population study

OBJECTIVES: To determine the carrier rate of the GJB2 mutation c.35delG and c.101T>C in a UK population study; to determine whether carriers of the mutation had worse hearing or otoacoustic emissions compared to non-carriers. DESIGN: Prospective cohort study. SETTING: University of Bristol, UK. PARTICIPANTS: Children in the Avon Longitudinal Study of Parents and Children. 9202 were successfully genotyped for the c.35delG mutation and c.101>T and classified as either carriers or non-carriers. OUTCOME MEASURES: Hearing thresholds at age 7, 9 and 11 years and otoacoustic emissions at age 9 and 11. RESULTS: The carrier frequency of the c.35delG mutation was 1.36% (95% CI 1.13 to 1.62) and c.101T>C was 2.69% (95% CI 2.37 to 3.05). Carriers of c.35delG and c.101T>C had worse hearing than non-carriers at the extra-high frequency of 16 kHz. The mean difference in hearing at age 7 for the c.35delG mutation was 8.53 dB (95% CI 2.99, 14.07) and 12.57 dB at age 9 (95% CI 8.10, 17.04). The mean difference for c.101T>C at age 7 was 3.25 dB (95% CI -0.25 to 6.75) and 7.61 dB (95% CI 4.26 to 10.96) at age 9. Otoacoustic emissions were smaller in the c.35delG mutation carrier group: at 4 kHz the mean difference was -4.95 dB (95% CI -6.70 to -3.21) at age 9 and -3.94 dB (95% CI -5.78 to -2.10) at age 11. There was weak evidence for differences in otoacoustic emissions amplitude for c.101T>C carriers. CONCLUSION: Carriers of the c.35delG mutation and c.101T>C have worse extra-high-frequency hearing than non-carriers. This may be a predictor for changes in lower-frequency hearing in adulthood. The milder effects observed in carriers of c.101T>C are in keeping with its classification as a mutation causing mild/moderate hearing loss in homozygosity or compound heterozygosity.