Airborne Infrared Scanning Imaging System with Rotating Drum for Fire Detection

Song, Chanho; Chang, Jun; Cao, Jian; Zhang, Lifei; Wen, Yao; Wei, Aman; Li, Jiang

doi:10.3807/josk.2011.15.4.340

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…(12). (12) The mean intensity value of the pixel assigned to class   is Lane Detection Algorithm for Night-time Digital Image Based on Distribution Feature … -Feng You et al 193 (13) Similarly, the mean intensity value of the pixel assigned to class   is (14) The cumulative mean up to level  is given by (15) And the average intensity of the entire image is given by (16) In order to evaluate the 'goodness' of the threshold at level  we use the normalized and dimensionless metric (17) Where    is the global variance (18) And    is the between-class variance, defined as …”

Section: Thresholding Based On Maximum Entropymentioning

confidence: 99%

Lane Detection Algorithm for Night-time Digital Image Based on Distribution Feature of Boundary Pixels

Feng¹,

Zhang²,

Zhong³

et al. 2013

Journal of the Optical Society of Korea

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This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions-horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.

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Section: Thresholding Based On Maximum Entropymentioning

confidence: 99%

Lane Detection Algorithm for Night-time Digital Image Based on Distribution Feature of Boundary Pixels

Feng¹,

Zhang²,

Zhong³

et al. 2013

Journal of the Optical Society of Korea

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Real-time computational processing and implementation for concealed object detection

et al. 2012

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Downloaded From: http://opticalengineering.spiedigitallibrary.org/ on 09/16/2013 Terms of Use: http://spiedl.org/termsAbstract. Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable computational processing would be required for automatic analysis of the images. The authors present statistical and computational algorithms and their implementations for real-time concealed object detection. The histogram of the image is modeled as a Gaussian mixture distribution, and hidden object areas are segmented by a multilevel scheme involving the expectation-maximization algorithm. The complete algorithm has been implemented in both MATLAB and C++. Experimental and simulation results confirm that the implemented system can achieve real-time detection of concealed objects.

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Frequency-domain compression imaging for extending the field of view of infrared thermometers

Huang¹,

Chang²,

Wu³

et al. 2023

Opt. Express

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We propose a computational imaging technique for expanding the field of view of infrared thermometers. The contradiction between the field of view and the focal length has always been a chief problem for researchers, especially in infrared optical systems. Large-area infrared detectors are expensive and technically arduous to be manufactured, which enormously limits the performance of the infrared optical system. On the other hand, the extensive use of infrared thermometers in COVID-19 has created a considerable demand for infrared optical systems. Therefore, improving the performance of infrared optical systems and increasing the utilization of infrared detectors is vital. This work proposes a multi-channel frequency-domain compression imaging method based on point spread function (PSF) engineering. Compared with conventional compressed sensing, the submitted method images once without an intermediate image plane. Furthermore, phase encoding is used without loss of illumination of the image surface. These facts can significantly reduce the volume of the optical system and improve the energy efficiency of the compressed imaging system. Therefore, its application in COVID-19 is of great value. We design a dual-channel frequency-domain compression imaging system to verify the proposed method's feasibility. Then, the wavefront coded PSF and optical transfer function (OTF) are used, and the two-step iterative shrinkage/thresholding (TWIST) algorithm is used to restore the image to get the final result. This compression imaging method provides a new idea for the large field of view monitoring systems, especially in infrared optical systems.

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Airborne Infrared Scanning Imaging System with Rotating Drum for Fire Detection

Cited by 3 publications

References 3 publications

Lane Detection Algorithm for Night-time Digital Image Based on Distribution Feature of Boundary Pixels

Lane Detection Algorithm for Night-time Digital Image Based on Distribution Feature of Boundary Pixels

Real-time computational processing and implementation for concealed object detection

Frequency-domain compression imaging for extending the field of view of infrared thermometers

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