• Journal of the Korea Society of Computer and Information
• /
• v.10 no.6 s.38
• /
• pp.187-194
• /
• 2005

The background subtraction method is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable environment factors such as gradually changing illumination, swaying trees and suddenly moving objects , which are to be considered for an adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background by considering adaptively the various changes in the scenes, and the adaptive GMMs improving the real-time Performance were Proposed and worked. This paper, for on-line background subtraction, employed the improved adaptive GMM, which uses the small constant for learning rate a and is not able to speedily adapt the suddenly movement of objects, So, this paper Proposed and evaluated the dynamic control method of a using the adaptive selection of the number of component distributions and the global variances of pixel values.

• The KIPS Transactions:PartB
• /
• v.12B no.5 s.101
• /
• pp.543-552
• /
• 2005

This paper proposes the extraction of coronary arteries based on DSA(Digital Subtraction Angiography) through a texture analysis of background in the angiography. DSA is a well established modality for the visualization of coronary arteries. DSA involves the subtraction of a mask image - an image of the heart before injection of contrast medium - from live image. However, this technique is sensitive to the movement of background and can result to a wrong detection by the variance of background gray-level intensity between two images. Therefore, this paper solves a structural problem resulted from a background movement bV selecting an image which has the least difference of movement through an analysis of the similarity of background texture and proposes a method to extract only the blood vessel efficiently through local gray-level correction of the selected image. Using the coronary angiogram of 5 patients clinical data, we proved that the proposed method has the lower false-detection rate, approximately $2\%$, and the higher accuracy than the existing methods.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.2
• /
• pp.83-92
• /
• 2013

RSA-CRT is a widely used algorithm that provides high performance implementation of the RSA-signature algorithm. Many previous studies on each operation step have been published to verify the physical leakages of RSA-CRT when used in smart devices. This paper proposes SAED (subtraction algorithm analysis on equidistant data), which extracts sensitive information using the event information of the subtraction operation in a reduction algorithm. SAED is an attack method that uses algorithm-dependent power signal changes. An adversary can extract a key using differential power analysis (DPA) of the subtraction operation. This paper indicates the theoretical rationality of SAED, and shows that its results are better than those of other methods. According to our experiments, only 256 power traces are sufficient to acquire one block of data. We verify that this method is more efficient than those proposed in previously published studies.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.3 no.1
• /
• pp.1-7
• /
• 2008

In this paper, a MSS-NOVO method that combines the HMM composition method with a noise reduction method is proposed for speech recognition in noisy environments. This combined method starts with noise reduction with modified spectral subtraction (MSS) to enhance the input noisy speech, then the noise and voice composition (NOVO) method is applied for making noise adapted models by using the noise in the non-utterance regions of the enhanced noisy speech. In order to evaluate the effectiveness of our proposed method, we compare MSS-NOVO method with other methods, i.e., SS-NOVO, MWF-NOVO. To set up the noisy speech for test, we add White noise to KLE 452 database with different SNRs range from 0dB to 15dB, at 5dB intervals. From the tests, MSS-NOVO method shows average improvement of 66.5% and 13.6% compared with the existing SS-NOVO method and MWF-NOVO method, respectively. Especially our proposed MSS-NOVO method shows a big improvement at low SNRs.

• Journal of Korea Multimedia Society
• /
• v.12 no.10
• /
• pp.1418-1426
• /
• 2009

There has been a lot of interest in an effective method for background subtraction in an effort to separate foreground objects from a predefined background image. Promising results on background subtraction using statistical methods have recently been reported are robust enough to operate in dynamic environments, but generally require very large computational resources and still have difficulty in obtaining clear segmentation of objects. We use a simple running-average method to model a gradually changing background, instead of using a complicated statistical technique. We employ a single global threshold vector, optimized by a genetic algorithm, instead of pixel-by-pixel thresholds. A new fitness function is defined and trained to evaluate segmentation result. The system has been implemented on a PC with a webcam, and experimental results on real images show that the new method outperforms an existing method based on a mixture of Gaussian.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.1
• /
• pp.18-23
• /
• 2010

Purpose: PET/CT combines functional and morphologic data and increases diagnostic accuracy in a variety of malignancies. Especially reconstructed Fusion PET/CT images or MIP (Maximum Intensity Projection) images from a 2-dimensional image to a 3-dimensional one are useful in visualization of the lesion. But in Fusion & MIP 3D reconstruction image, due to hot uptake by urine or urostomy bag, lesion is overlapped so it is difficult that we can distinguish the lesion with the naked eye. This research tries to improve a distinction by removing parts of hot uptake. Materials and Methods: This research has been conducted the object of patients who have went to our hospital from September 2008 to March 2009 and have a lot of urine of remaining volume as disease of uterus, bladder, rectum in the result of PET/CT examination. We used GE Company's Advantage Workstation AW4.3 05 Version Volume Viewer program. As an analysis method, set up ROI in region of removal in axial volume image, select Cut Outside and apply same method in coronal volume image. Next, adjust minimum value in Threshold of 3D Tools, select subtraction in Advanced Processing. It makes Fusion & MIP images and compares them with the image no using Region Cut Definition. Results: In Fusion & MIP 3D reconstruction image, it makes Fusion & MIP images and compares them by using Advantage Workstation AW4.3 05's Region Cut Subtraction, parts of hot uptake according to patient's urine can be removed. Distinction of lesion was clearly reconstructed in image using Region Cut Definition. Conclusion: After examining the patients showing hot uptake on account of volume of urine intake in bladder, in process of reconstruction image, if parts of hot uptake would be removed, it could contribute to offering much better diagnostic information than image subtraction of conventional method. Especially in case of disease of uterus, bladder and rectum, it will be helpful for qualitative improvement of image.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.2
• /
• pp.180-186
• /
• 2004

The presence of noise in speech signals degrades the performance of recognition systems in which there are mismatches between the training and test environments. To make a speech recognizer robust, it is necessary to compensate these mismatches. In this paper, we studied about an improvement of stochastic feature extraction based on band-SNR for robust speech recognition. At first, we proposed a modified version of the multi-band spectral subtraction (MSS) method which adjusts the subtraction level of noise spectrum according to band-SNR. In the proposed method referred as M-MSS, a noise normalization factor was newly introduced to finely control the over-estimation factor depending on the band-SNR. Also, we modified the architecture of the stochastic feature extraction (SFE) method. We could get a better performance when the spectral subtraction was applied in the power spectrum domain than in the mel-scale domain. This method is denoted as M-SFE. Last, we applied the M-MSS method to the modified stochastic feature extraction structure, which is denoted as the MMSS-MSFE method. The proposed methods were evaluated on isolated word recognition under various noise environments. The average error rates of the M-MSS, M-SFE, and MMSS-MSFE methods over the ordinary spectral subtraction (SS) method were reduced by 18.6%, 15.1%, and 33.9%, respectively. From these results, we can conclude that the proposed methods provide good candidates for robust feature extraction in the noisy speech recognition.

• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.4 s.32
• /
• pp.133-139
• /
• 2004

In this paper. we propose a medical image processing method for detection of periodontal disease by geometric analysis on dental digital radiography. This paper proposes the method of an automatic image alignment and detection of minute changes, to overcome defects in the conventional subtraction radiography by image processing technique, that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the geometric features in target images. Therefore, we use these methods because they give accuracy, consistency and objective information or data to results. In result, easily and visually we can identify minute differences in the affected parts whether they have problems or not, and using application system.

• KIISE Transactions on Computing Practices
• /
• v.22 no.3
• /
• pp.133-138
• /
• 2016

Motion detection algorithms based on difference image are classified into background subtraction and previous frame subtraction. 1) Background subtraction is a convenient and effective method for detecting foreground objects in a stationary background. However in real world scenarios, especially outdoors, this restriction, (i.e., stationary background) often turns out to be impractical since the background may not be stable. 2) Previous frame subtraction is a simple technique for detecting motion in an image. The difference between two frames depends upon the amount of motion that occurs from one frame to the next. Both these straightforward methods fail when the object moves very "slightly and slowly". In order to efficiently deal with the problem, in this paper we present an algorithm for motion detection that incorporates "reflected light area" and "difference image". This reflected light area is generated during the frame production process. It processes multiplex difference image and AND-arithmetic of bitwise. This process incorporates the accuracy of background subtraction and environmental adaptability of previous frame subtraction and reduces noise generation. Also, the performance of the proposed method is demonstrated by the performance assessment of each method using Gait database sample of CASIA.