Applications of a morphological scene change detection (MSCD) for visual leak and failure identification in process and chemical engineering

Tickle, Andrew J.; Harvey, Paul K.; Smith, Jeremy S.

doi:10.1117/12.864994

Cited by 3 publications

(2 citation statements)

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“…Dilation imposes the structuring element over each pixel and if any pixels inside the are '1' then the output is also '1'. The equation for morphological dilation is [3]: (2) Where is the image, represents the structuring element covering area . The output is ON when the pixel is ON or when any pixels contained within the area are ON.…”

Section: 1mentioning

confidence: 99%

“…This previous system was found to fail however when operating in low light conditions, the aim of the work presented here is to suggest modifications that could remove this limitation to allow the application to be more effective for many different tasks. The system has already shown potential to detect leaks from pipes [2] in the chemical or nuclear industry, in addition to being augmented with digital watermarking capabilities in order to make the images stand up better in a court of law. When implemented on embedded systems, MSCD systems are an inexpensive way to help secure an environment.…”

Section: Introductionmentioning

confidence: 98%

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Morphological scene change detection for night time security

Jarvis

Tickle

2012

SPIE Proceedings

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Morphological Scene Change Detection (MSCD) systems can be used to secure environments by sensing potential intruders and alerting security personnel to any security risks. To achieve this, the system compares the input from a camera to a reference image quantifying the level of change between the images, raising the alarm if this change is greater than a set triggering level. Morphological operators are than used to reduce the effect of any image change not related to a potential security risk; this includes noise and other minor changes thus decreasing the risk of false alarms. However in low light conditions MSCD systems can fail due to the reduced intensity differences between images containing security threats and reference images. This paper documents a proof of concept for a system that would use night vision images to address this problem. Here a low light scope camera attachment is used in place of a night vision camera and shows modifications to the previous MSCD system, which improves the performance when used with night vision images. The analysis of the modified system's performance in different low light environments, this includes analysis of appropriate binary threshold and alarm triggering levels for a range of environments. The latter includes indoors at a distance, indoors at close range, outdoors at a distance and outdoors at close range. The results shown demonstrate that MSCD systems operating in low light conditions have the potential to be used as a useful tool in a security system and are compared to the original to demonstrate the improvement.

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Section: 1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%