• The Journal of the Korea institute of electronic communication sciences
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• 제8권4호
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• pp.555-560
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• 2013

This paper first proposes a classification algorithm which detects a voiced, unvoiced, and silence signal using distance measure, logarithm power and root mean square methods at each frame, then a spectrum subtraction algorithm based on a subband filter. The proposed algorithm subtracts spectrums of white noise and street noise from noisy signal based on the subband filter at each frame. In this experiment, experimental results of the proposed spectrum subtraction algorithm demonstrate using the speech and noise data of Aurora-2 database. Based on measuring the speech-to-noise ratio (SNR), experiments confirm that the proposed algorithm is effective for the speech by contaminated the noise. From the experiments, the improvement in the output SNR values was approximately 2.1 dB and 1.91 dB better for white noise and street noise, respectively.

• The KIPS Transactions:PartB
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• 제11B권3호
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• pp.275-280
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• 2004

In this paper, we propose automatic subtraction radiography algorithms to overcome conventional subtraction radiography's defects by applying image processing technique. In order to reach these goals, this paper suggests the image alignment method that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the structure characteristics in target images. Therefore, we use these methods because they give accurary, consistency and objective information or data to results. According to the results, easily and visually we can identify fine difference int the affected parts wether they have problems or not.

• Proceedings of the Korean Society of Medical Physics Conference
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• 한국의학물리학회 2002년도 Proceedings
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• pp.335-337
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• 2002

The aim of this study was investigate the epileptogenic zone in temporal lobe epilepsy (TLE). We evaluated the subtraction image of interictal SPECT from ictal SPECT coregistered to 3-dimensional (3D) MRI, and compared with the normal healthy SPECT using a SPM99. Forty-nine patients with TLE (M:F=28:21, mean age: 33${\pm}$2.1 years) underwent a pairs of ictal and interictal SPECT. We performed subtraction interictal SPECT from ictal SPECT in TLE patients. In addition, using SPM methods and t-statistics, SPECT images of the TLE patients were compared with normal healthy SPECT on a voxel by voxel basis. The voxels with a p-value of less than 0.05, 0.005, 0.001 were considered to be significantly different. The subtraction results by ictal and interictal SPECT coincided with the significant rCBF changes when compare of the normal healthy SPECT using a SPM99. The results suggested that analysis of difference of the two methods using healthy normal SPECT with SPM99 is useful tool in evaluation of seizure focus in epilepsy.

• Speech Sciences
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• 제15권2호
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• pp.67-77
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• 2008

In this paper, we implemented a robust speech recognizer using the TMS320VC33 DSP. For this implementation, we had built speech and noise database suitable for the recognizer using spectral subtraction method for noise removal. The recognizer has an explicit structure in aspect that a speech signal is enhanced through spectral subtraction before endpoints detection and feature extraction. This helps make the operation of the recognizer clear and build HMM models which give minimum model-mismatch. Since the recognizer was developed for the purpose of controlling car facilities and voice dialing, it has two recognition engines, speaker independent one for controlling car facilities and speaker dependent one for voice dialing. We adopted a conventional DTW algorithm for the latter and a continuous HMM for the former. Though various off-line recognition test, we made a selection of optimal conditions of several recognition parameters for a resource-limited embedded recognizer, which led to HMM models of the three mixtures per state. The car noise added speech database is enhanced using spectral subtraction before HMM parameter estimation for reducing model-mismatch caused by nonlinear distortion from spectral subtraction. The hardware module developed includes a microcontroller for host interface which processes the protocol between the DSP and a host.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• 제24권2호
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• pp.305-316
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• 1994

The comparative detectability of the artificial defects among conventional radiographs, digital images and digital subtraction images was evaluated. The artificial defects were made within spogy bone of 24 unilateral mandibles of adult dogs. The results were as follows: 1. With normal exposure time, the detectability of digital subtraction radiographs was 90.3% which was statistically significant superior to those of conventional radiographs(78.0%) and digital images(75.9%) (p<0.05). 2. With half-exposure time, the detectability of conventional radiographs, digital images and digital subtraction radiographs was 68.4%, 67.3% and 69.9% respectively. There was no statistical significant difference among the detectability of these methods(p>0.05). 3. All radiographic images with normal exposure time showed statistically significant superior detectability to those with half-exposure time(p<0.05). 4. The detectability of digital subtraction radiographs was not linearly related to the standard deviation of the grey levels of reference line(p<0.05).

• Journal of Biomedical Engineering Research
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• 제26권4호
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• pp.199-205
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• 2005

When recording single-unit responses from neural systems, a common problem is the accurate detection of spikes (action potentials) in the presence of competing unwanted (noise) signals. While some sources of noise can be readily dealt with through filtering or 'template subtraction' techniques, other sources present a more difficult problem. In particular, noise components introduced by power supplies, which contain harmonics of the power-line frequency, can be particularly troublesome in that they can mimic the shape of the desired spikes. Thus, standard 'template subtraction' techniques or notch-filtering approaches are not appropriate. In this study, we propose the use of a novel template-subtraction scheme that involves estimating the power-line noise waveform and using cross-correlation techniques to subtract them from the recordings. This technique requires two key steps: (1) cross-correlation analysis of each recorded waveform extracts a robust representation of the power-line noise waveform and (2) a second level of cross-correlation to successfully subtract that representation from each recorded waveform. This paper describes this algorithm and provides examples of its implementation using actual recorded waveforms that are contaminated with these noise signals. An improvement (reduction) in the noise level is reported, as are suggestions for future implementation of this strategy.

• The Korean Journal of Emergency Medical Services
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• 제21권2호
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• pp.89-102
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• 2017

Purpose: The purpose of the study was to investigate the effects of subtraction meditation on perceived stress, self-efficacy, blood pressure, and pulse rate in paramedic students. Methods: A quasi-experimental study with non-equivalent comparison groups using pre and post-test design was performed. The experimental group consisted of 27 participants who attended the meditation program, and the control group consisted of 26 non-participants of the program. The data were analyzed using SPSS/WIN 24.0. Results: There were a statistically significant differences between the experimental group and the control group in perceived stress(t=2.301, p=.026), systolic pressure(F=18.531, p=.000), diastolic pressure(F=9.745, p=.003), and pulse rate(F=33.869, p=.000) between pretest and posttest results. Conclusion: The subtraction meditation program can help reduce perceived stress, systolic pressure, diastolic pressure, and pulse rate.

• Journal of Institute of Control, Robotics and Systems
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• 제21권8호
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of Institute of Control, Robotics and Systems
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• 제16권1호
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제13권10호
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• pp.2211-2217
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• 2009

In this paper, we propose the speech enhancement algorithm using an one-microphone in a reverberant room environments. Spectral subtraction is the effective method which can reduce the reverberation element and the noise in a spectrum domain. Spectral subtraction needs correct separation of voice section and silent section therefore to improve the performance, voice activity detection(VAD) based on entropy has been applied to the proposed method. We test a performance of the proposed method by comparing with conventional method which used VAD based on energy detection. Reverberation reduction ratio with variable of SNR and a reverberation time is used as a test index. From the simulation result, proposed method shows performance better than conventional method.