Geza Varady

Mesopic visual efficiency IV: A model with relevance to nighttime driving and other applications

The authors represent a research consortium1 which has adopted a task performance based approach for nighttime driving to establish a system for photometry in the mesopic region. This article analyses the experimental investigations described in earlier articles on visual performance in the mesopic domain using reaction time, detection threshold, and discrimination threshold techniques. These results are used to develop a system for mesopic photometry, which balances the quality of the fit to the experimental data with the ease of practical implementation by the lighting industry. A more complex model is also described, which takes account of the chromatic visual response channels and thus provides a better fit to some of the experimental results (particularly those involving monochromatic stimuli), but describes the totality of the data less well and is furthermore less suitable for practical photometric measurements.

Mesopic models : from brightness matching to visual performance in night-time driving: a review

At present, suitable methods to evaluate the visual effectiveness of lighting products in the mesopic region are not available. The majority of spectral luminous efficiency functions obtained to date in the mesopic range have been acquired by heterochromatic brightness matching. However, the most recent studies in the mesopic field have adopted a task performance-based approach. This paper summarizes the major mesopic models proposed so far, presenting in detail the experimental conditions of these studies. The authors represent a research consortium which has adopted the task performance-based approach for night-time driving in which mesopic visual performance has been divided into three subtasks. Data for each sub-task will be generated by using a set of common parameter values and 120 observers. The approach and methods used by the consortium are presented.

Mesopic spectral sensitivity functions based on visibility and recognition contrast thresholds

Human vision works in a complex way in the mesopic luminance range which is not yet clearly understood, although several important visual tasks are performed at these luminance levels. In this study, spectral data for detection visibility and recognition contrast sensitivity were obtained in visual experiments. From our data it appears that chromatic channels also influence mesopic contrast sensitivity. An achromatic model of spectral sensitivity is fitted to our experimental data and the remaining chromatic components are discussed.

Effect of chromatic mechanisms on the detection of mesopic incremental targets at different eccentricities.

Spectral sensitivity functions for the threshold detection of mesopic incremental targets were compared for different target eccentricities (10, 20, and 30°) and for different mesopic backgrounds (0.1, 0.5 and 1.0 cd m−2). Relative responsivities of achromatic mechanisms (L + M and rods) and chromatic mechanisms (S and |L–M|) were estimated for each eccentricity and background. Chromatic mechanisms contribute significantly to detection but their effect is lower at 30°. A new contrast metric (CCHC2) is introduced to account for the selective adaptation of the photoreceptors and the effects of the chromatic mechanisms i.e. broadening of the range of spectral sensitivity with multiple local maxima and yellow sub‐additivity of detection performance. The CCHC2 metric is compared with the achromatic contrast metric of the MOVE model (CMOVE). For the same target, CCHC2 generally predicts a higher visibility level than CMOVE. However, in accordance with visual observations, for grey or yellowish incremental targets appearing at the eccentricities of 20 and 30°, the visibility predicted by CCHC2 is less than the visibility predicted by CMOVE.

Authors’ response to SA Fotios

three sub-tasks: can it be seen, how quickly, and what is it. This provides a useful framework for devising the experimental work. Would the authors please confirm whether the proposed reaction time tests will be onaxis, off-axis, or both. Also, it is noted several times that their work will use 120 observers: is this particular quantity significant, and if so, why? I look forward to reading the results of the experimental work described in this paper.

Histogram based segmentation of shadowed leaf images

This paper corresponds to the solution of some problems realized during ragweed identification experiments, namely the samples collected on the field by botanical experts did not match the initial conditions expected. Reflections and shadows appeared on the image, which made the segmentation more difficult, therefore also the classification was not efficient in previous study. In this work, unlike those solutions, which try to remove the shadow by restoring the illumination of image parts, the focus is on separating leaf and background points based on chromatic information, basically by examining the histograms of the full image and the border. This proposed solution filters these noises in the subspaces of hue, saturation and value space and their combination. It also describes a qualitative technique to select the appropriate values from the filtered outputs. With this method, the results of segmentation improved a lot.

Phase plane tuning of fuzzy controller for 1 DoF helicopter model

The paper suggests a design procedure for fuzzy cascade control. The expert knowledge based tuning procedure is supported by investigation the phase plane of the reference tracking. The plant is a one degree of freedom helicopter model with highly non-linear dynamics in a hardware-in-the-loop arrangement. Starting from a common fuzzy-PI controller in the outer loop and classic PI-controller in the inner loop, the presented tuning procedure enables to obtain fuzzy-adaptive parameter settings of the inner-loop and a heuristic modified rule base in the outer loop. The developed control strategy proves to be very successful: both the settling times and overshoots have become well regulated.