• Journal of the Korea Society of Computer and Information
• /
• v.23 no.1
• /
• pp.25-32
• /
• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.991-994
• /
• 2009

This paper reports of camera detection of Mura. The type, location, size, orientation and amplitude are found. As the luminance variation in Mura is down to less than app. 0.3 %, measurement apparatus, techniques and algorithms are developed to measure low noise data and to extract the Mura from data with the residual noise in the same magnitude as the Mura.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.5
• /
• pp.447-453
• /
• 2009

This paper introduces the method for detect voices and exact end point at low SNR by maximizing voice energy. Conventional VAD (Voice Activity Detection) algorithm estimates noise level so it tends to detect the end point inaccurately. Moreover, because it uses relatively long analysis range for reflecting temporal change of noise, computing load too high for application. In this paper, the SEM-VAD (Speech Energy Maximization-Voice Activity Detection) method which uses psycho-acoustical bark scale filter banks to maximize voice energy within frames is introduced. Stable threshold values are obtained at various noise environments (SNR 15 dB, 10 dB, 5 dB, 0 dB). At the test for voice detection in car noisy environment, PHR (Pause Hit Rate) was 100%accurate at every noise environment, and FAR (False Alarm Rate) shows 0% at SNR15 dB and 10 dB, 5.6% at SNR5 dB and 9.5% at SNR0 dB.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.985-990
• /
• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.327-332
• /
• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than loom.

• Journal of KIISE
• /
• v.42 no.7
• /
• pp.868-877
• /
• 2015

The barcode area extraction from images has been extensively studied, and existing methods exploit frequency characteristics or depend on the Hough transform (HT). However, the slantedness of the images and noise affects the performance of these approaches. Moreover, it is difficult to deal with the case where an image contains multiple barcodes. We therefore propose a barcode detection algorithm that is robust under such unfavorable conditions. The pre-processing step implements a probabilistic Hough transform to determine the areas that contain barcodes with a high probability, regardless of the slantedness, noise, and the number of instances. Then, a frequency component analysis extracts the barcodes. We successfully implemented the proposed system and performed a series of barcode extraction tests.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2010.10a
• /
• pp.533-534
• /
• 2010

Fiber optic sensor has bee widely used in the industrial applications. For the application of acoustic detection of the high voltage electric transformer Sagnac interferometer can be used. In this paper several different materials of mandrel were used in the fiber sensor array. Based on the transformer oil fiber optic sensor is more sensitive than in the air.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.367-369
• /
• 2005

In this paper, we present a new method for the detection of spiculation on digital mammograms. Traditional methods have defects; sensitive to noise, fixed size processing, and long processing time, however, the proposed method has merits; not sensitive to noise, adaptive size processing, and fast processing time. Experimental results show that the spiculation detection performance of the proposed method is improved much compared to the other methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.4
• /
• pp.817-822
• /
• 2011

This paper first proposes the speech recognition algorithm by detection of the speech and noise sections at each frame using a neural network training by back-propagation algorithm, then proposes the spectral subtraction method which removes the noises at each frame according to detection of the speech and noise sections. In this experiment, the performance of the proposed recognition system was evaluated based on the recognition rate using various speeches that are degraded by white noise and car noise. Moreover, experimental results of the noise reduction by the spectral subtraction method demonstrate using the speech and noise sections detecting by the speech recognition algorithm at each frame. Based on measuring signal-to-noise ratio, experiments confirm that the proposed algorithm is effective for the speech by corrupted the noise using signal-to-noise ratio.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.959-962
• /
• 2012

In the process of image acquisition, transmission and storage, image degradation occurs due to various reason, the mainly reason is noise. To restore basic methods used images of impulse noise pollution by SM, AF, CWMF. In this paper, using the modified filter to remove impulse noise. The method consists of detection and noise filtering of the noise signal. For a non-noise signal is intact, the noise signal is filtered according to the algorithm. And then through the simulation is compared with known basic methods, with PSNR as judged by reference.