Smoke detecting apparatus

• US 8,208,723 B2
• Filed: 10/14/2009
• Issued: 06/26/2012
• Est. Priority Date: 10/14/2008
• Status: Expired due to Fees

• Current Assignee: Nohmi Bosai Limited (Secom Company Limited), University of Tokushima
• Original Assignee: Nohmi Bosai Limited (Secom Company Limited), University of Tokushima
• Inventors: Yamagishi, Takatoshi, Nakano, Kazuhisa, Terada, Kenji
• Primary Examiner(s): Do, Anh Hong
• Application Number:
  US12/578,850
• Publication Number:
  US 20100098335A1
• Time in Patent Office: 986 Days
• Field of Search: 382/100, 382/168, 382/218, 382/286, 356/438, 348/143, 348/165, 348/154, 340/577, 340/578, 340/630
• US Class Current: 382/168
• CPC Class Codes: G08B 17/125 by using a video camera to detect fire or smoke

Abstract

Provided is a smoke detecting apparatus capable of detecting occurrence of smoke at high sensitivity while suppressing an effect of disturbance. The smoke detecting apparatus for detecting occurrence of smoke by subjecting an image captured by a monitoring camera to image processing includes: an image memory (10) for storing a plurality of images captured by the monitoring camera in a time series; and a smoke detection area selecting portion (20) for calculating a luminance histogram of the same pixel for each predetermined pixel a plurality of times in a past predetermined period based on the plurality of images stored in the image memory (10), detecting presence or absence of a luminance value that has been newly generated due to occurrence of one of an intrusive object and smoke based on the luminance histogram, and identifying candidate regions to be subjected to the image processing.

Claims

1. A smoke detecting apparatus for detecting occurrence of smoke by subjecting an image captured by a monitoring camera to image processing, the smoke detecting apparatus comprising:

an image memory for storing a plurality of images captured by the monitoring camera in a time series; and

a smoke detection area selecting portion for calculating a luminance histogram of the same pixel for each predetermined pixel a plurality of times in a past predetermined period based on the plurality of images stored in the image memory, detecting presence or absence of a luminance value that has been newly generated due to occurrence of one of an intrusive object and smoke based on the luminance histogram, and identifying candidate regions to be subjected to the image processing.

2. The smoke detecting apparatus according to claim 1, wherein the smoke detection area selecting portion comprises:

luminance histogram creating means for calculating the luminance histogram;

luminance change judging means for detecting the presence or absence of the luminance value that has been newly generated due to the occurrence of the one of the intrusive object and smoke based on the luminance histogram that has been individually calculated for the each predetermined pixel by the luminance histogram creating means, and mapping pixels having the newly generated luminance value; and

detection candidate region identifying means for determining a ratio of the pixels which have been mapped by the luminance change judging means to have the newly generated luminance value, for each predetermined area including a plurality of pixels, and identifying regions having the ratio equal to or higher than a predetermined value as the candidate regions to be subjected to the image processing.

3. The smoke detecting apparatus according to claim 1, further comprising a smoke occurrence detecting portion for calculating a feature value regarding smoke for each of the regions identified as the candidate regions in the image captured by the monitoring camera, and judging presence or absence of smoke occurrence based on a result of the calculation.

4. The smoke detecting apparatus according to claim 3, wherein the smoke occurrence detecting portion comprises:

smoke feature value calculating means for extracting the feature value regarding smoke for each of the candidate regions, and judging whether or not the each of the candidate regions has a high probability of smoke occurrence based on a result of the extraction;

mapping means for mapping regions judged by the smoke feature value calculating means to have the high probability of smoke occurrence; and

smoke judging means for judging that smoke has occurred if the regions judged to have the high probability of smoke occurrence and mapped by the mapping means are detected across a predetermined number of regions over a predetermined continuous period of time.

5. The smoke detecting apparatus according to claim 4, wherein:

the smoke feature value calculating means extracts a plurality of feature values as the feature value to judge whether or not the each of the candidate regions has the high probability of smoke occurrence; and

the mapping means maps regions judged to have the high probability of smoke occurrence in common with respect to a certain combination of respective judgment results based on the plurality of feature values.

6. A smoke detecting apparatus, comprising:

smoke feature value calculating means for extracting a feature value regarding smoke for each of a plurality of regions set in an image captured by a monitoring camera;

a storage portion storing a plurality of predetermined reference judgment values having a plurality of detection sensitivities for the each of the plurality of regions, for judging presence or absence of smoke occurrence for the each of the plurality of regions;

region-to-region sensitivity setting means for setting a desired detection sensitivity for the each of the plurality of regions depending on an object to be monitored by the monitoring camera; and

smoke judging means for retrieving a predetermined reference judgment value corresponding to the desired detection sensitivity set by the region-to-region sensitivity setting means from among the plurality of predetermined reference judgment values stored in the storage portion, comparing the retrieved predetermined reference judgment value with the feature value extracted by the smoke feature value calculating means, and detecting smoke occurrence at the desired detection sensitivity for the each of the plurality of regions based on a result of the comparison, for the each of the plurality of regions.

7. The smoke detecting apparatus according to claim 6, further comprising disturbance occurrence detecting means for calculating a feature value for discriminating whether or not a temporal change in luminance in the each of the plurality of regions is due to an effect of disturbance other than the smoke occurrence based on time-series data of a plurality of the images captured by the monitoring camera in a time series, and judging whether or not the effect of disturbance has occurred based on a result of comparing the feature value and a predetermined reference value,

wherein, in retrieving one reference judgment value from among the plurality of predetermined reference judgment values stored in the storage portion, the smoke judging means retrieves a reference judgment value having a detection sensitivity lower than the desired detection sensitivity set by the region-to-region sensitivity setting means to detect the smoke occurrence at the detection sensitivity lower than the desired detection sensitivity in the region in which the effect of disturbance is judged to have occurred by the disturbance occurrence detecting means.

8. The smoke detecting apparatus according to claim 7, wherein the disturbance occurrence detecting means calculates an amount of change in average luminance as the feature value for the each of the plurality of regions based on the time-series data, and judges that an illumination change has occurred as the effect of disturbance when the amount of change in average luminance one of increases and decreases monotonously to a predetermined amount.

9. The smoke detecting apparatus according to claim 7, wherein the disturbance occurrence detecting means sequentially calculates a correlated luminance value between a preceding cycle and a current cycle as the feature value based on the time-series data, and judges that temporary occlusion by a moving object occurs as the effect of disturbance if an amount of change in the correlated luminance value is equal to or higher than a predetermined value.