Digital image analysis of flatfish bleeding injury

To improve accuracy of post-release mortality predictions and facilitate the routine collection of information about physical condition of catches after commercial fishing capture, traditional visual assessment by potentially subjective human observers or raters may be automated by digital image analysis. The purpose of this study was to develop a method and device that can eliminate subjectivity in scoring external injury of commercially beam-trawled flatfish by taking standardized, high resolution images to allow for automated calculation of the % surface area of visible bleeding injury relative to the whole fish based on digital image analysis. A reference library was compiled by photographing ventral sides of 67 fish of six flatfish species of different sizes and freshness (fresh vs defrosted). All fish were sourced from the R/V Simon Stevin while beam-trawling in the Belgian coastal zone of the Southern North Sea. All images that were neither over- nor under-exposed were compiled (n = 51) and scored for the extent (%) of multifocal cutaneous petechial ('point bleeding'), and suffusion or haemorrhaging ('bruising') of the ventral head and body region, respectively, by three experienced raters using a continuous scale (between 0 and 100 %). Then, several state-of-the-art computer vision algorithms were tested on the dataset to develop a protocol that can 1) align each image; 2) identify fin, body and head regions; and 3) quantify the surface area of bleeding injury of each region by using appropriate thresholding techniques. For validation of the computer-derived % surface coverage estimates of bleeding injury, these were compared to the average rater's score. For bruising injury, a significant difference between human- vs computer-derived scores persisted. For point bleeding of the head region, computer-based estimates of % coverage were not different from those of the human raters. Overall, species, size and their freshness did not have a significant effect. By consistently recording the coverage of externally visible bleeding injury, this image analysis protocol may find its application in measuring the effect of different capture techniques on whole fish quality, and in improving vitality assessments as part of the transition towards a more sustainable fishery and the implementation of the European Landing Obligation

Video fire detection - Review

Cataloged from PDF version of article.This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor “volumes” and do not have transport delay that the traditional “point” sensors suffer from. It is possible to cover an area of 100 km2 using a single pan-tiltzoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation. © 2013 Elsevier Inc. All rights reserve

DATA ASSIMILATION BASED NUMERICAL SIMULATIONS TO ASSIST REAL-TIME SMOKE CONTROL MANAGEMENT IN LARGE SPACES

Abstract The work presented in this paper illustrates the concept of numerical simulations for real-time 'Numerical Fire Forecast' (NFF), applied to smoke control management in large spaces. The numerical calculations performed within the Inverse Zone Modelling framework are based on a series of full scale experiments conducted using the Japanese Building Research Institute (BRI) fire test facility. The experimental set-up consists of a large space of 720m 2 floor area and 26.3m ceiling height, equipped with shafts and fans to study different smoke control options. The measurements include the smoke layer interface (from thermocouples, photometers and visual observation), the smoke layer temperature at different heights (using thermocouples) and the mass flows of air and hot smoke through mechanical and natural vents. In the case of natural filling (i.e. no mechanical or natural venting), the assimilation of smoke layer height data within a 30 s window results in more than 4 minutes lead time of the forecast, with a good level of confidence. Predictions are given in terms of smoke layer height and upper layer temperature. The steady-state value of the methanol fire (Q c = 1300 kW) has been estimated after 30 s with less than 10% error. Widening the assimilation window does not improve the forecast. When mechanical ventilation is activated after the assimilation process with a sufficiently high exhaust rate, the forecast shows with a relatively substantial positive lead time, safe levels of smoke interface height. Introduction Fire Safety Engineering is a multi-disciplinary science, which aims at designing fire-safe buildings with appropriate solutions to preserve property and, most importantly, human life. Therefore, before the construction (or the renovation) of a building, architects, fire engineers and regulators need to consider a given set of fire scenarios in order to examine different options and choose the most appropriate one(s). For this purpose, a large amount of tools have been developed across the years in order to provide an answer to various questions that arise when studying the complex phenomenon of a fire. These questions are often related to the integrity of the building (fire resistance of the structure), fire and smoke spread, and evacuation. The tools used range from simple engineering hand-calculations to the more sophisticated computational fluid and solid mechanics. Many fire simulation tools have been developed to provide guidance in a priori studies. The level of complexity already reached in these tools and the required computational resources render their use for real time predictions impossible. Subsequently, fire fighters have to rely on their intuition and experience as to the decisions and actions to take in real fire situations. It is in this context that the concept of sensor assisted fire fighting has emerge

Video fire detection - Review

This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor "volumes" and do not have transport delay that the traditional "point" sensors suffer from. It is possible to cover an area of 100 km2 using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation. © 2013 Elsevier Inc. © 2013 Elsevier Inc. All rights reserved

A multi-modal video analysis approach for car park fire detection

In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by visual flame feature analysis and amplitude disorder detection. In order to detect the low-cost flame related features, moving objects in visual images are analyzed over time. If an object possesses high probability for each of the flame characteristics, it is labeled as candidate flame region. Simultaneously, the amplitude disorder is also investigated. Also labeled as candidate flame regions are regions with high accumulative amplitude differences and high values in all detail images of the amplitude image's discrete wavelet transform. Finally, when there is overlap of at least one of the visual and amplitude candidate flame regions, fire alarm is raised. The smoke detector, on the other hand, focuses on global changes in the depth images of the time-of-flight camera, which do not have significant impact on the amplitude images. It was found that this behavior is unique for smoke. Experiments show that the proposed detectors improve the accuracy of fire detection in car parks. The flame detector has an average flame detection rate of 93%, with hardly any false positive detection, and the smoke detection rate of the TOF based smoke detector is 88%. © 2012 Elsevier Ltd