• Title/Summary/Keyword: Noise detection algorithm

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A Modified Viterbi Algorithm for Word Boundary Detection Error Compensation (단어 경계 검출 오류 보정을 위한 수정된 비터비 알고리즘)

  • Chung, Hoon;Chung, Ik-Joo
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.1E
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    • pp.21-26
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    • 2007
  • In this paper, we propose a modified Viterbi algorithm to compensate for endpoint detection error during the decoding phase of an isolated word recognition task. Since the conventional Viterbi algorithm explores only the search space whose boundaries are fixed to the endpoints of the segmented utterance by the endpoint detector, the recognition performance is highly dependent on the accuracy level of endpoint detection. Inaccurately segmented word boundaries lead directly to recognition error. In order to relax the degradation of recognition accuracy due to endpoint detection error, we describe an unconstrained search of word boundaries and present an algorithm to explore the search space with efficiency. The proposed algorithm was evaluated by performing a variety of simulated endpoint detection error cases on an isolated word recognition task. The proposed algorithm reduced the Word Error Rate (WER) considerably, from 84.4% to 10.6%, while consuming only a little more computation power.

Noise Mitigation for Target Tracking in Wireless Acoustic Sensor Networks

  • Kim An, Youngwon;Yoo, Seong-Moo;An, Changhyuk;Wells, Earl
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.5
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    • pp.1166-1179
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    • 2013
  • In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

PVC Classification Algorithm Through Efficient R Wave Detection

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of Sensor Science and Technology
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    • v.22 no.5
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    • pp.338-345
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    • 2013
  • Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

Voice Activity Detection Algorithm using Fuzzy Membership Shifted C-means Clustering in Low SNR Environment (낮은 신호 대 잡음비 환경에서의 퍼지 소속도 천이 C-means 클러스터링을 이용한 음성구간 검출 알고리즘)

  • Lee, G.H.;Lee, Y.J.;Cho, J.H.;Kim, M.N.
    • Journal of Korea Multimedia Society
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    • v.17 no.3
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    • pp.312-323
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    • 2014
  • Voice activity detection is very important process that find voice activity from noisy speech signal for noise cancelling and speech enhancement. Over the past few years, many studies have been made on voice activity detection, it has poor performance for speech signal of sentence form in a low SNR environment. In this paper, it proposed new voice activity detection algorithm that has beginning VAD process using entropy and main VAD process using fuzzy membership shifted c-means clustering. We conduct an experiment in various SNR environment of white noise to evaluate performance of the proposed algorithm and confirmed good performance of the proposed algorithm.

Edge Detection Method using Modified Coefficient Masks (변형된 계수 마스크를 이용한 에지 검출 방법)

  • Lee, Chang-Young;Chung, Suk-Moon;Kim, Nam-Ho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.218-223
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    • 2013
  • The performances of previous edge detection methods such as Sobel, Prewitt, and LoG(Laplacian of Gaussian) are insufficient for images degraded in AWGN(additive white Gaussian noise). Therefore, in this paper, we proposed an edge detection algorithm using a modified coefficient masks with gradient masks and distance weight mask. In order to confirm and verify the performance of the proposed algorithm, we simulated and compared proposed algorithm to conventional methods on various standard images added AWGN with a standard deviation ${\sigma}$=15, 30 and proposed algorithm shows superior edge detection characteristics in processed images.

Depth-map Preprocessing Algorithm Using Two Step Boundary Detection for Boundary Noise Removal (경계 잡음 제거를 위한 2단계 경계 탐색 기반의 깊이지도 전처리 알고리즘)

  • Pak, Young-Gil;Kim, Jun-Ho;Lee, Si-Woong
    • The Journal of the Korea Contents Association
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    • v.14 no.12
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    • pp.555-564
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    • 2014
  • The boundary noise in image syntheses using DIBR consists of noisy pixels that are separated from foreground objects into background region. It is generated mainly by edge misalignment between the reference image and depth map or blurred edge in the reference image. Since hole areas are generally filled with neighboring pixels, boundary noise adjacent to the hole is the main cause of quality degradation in synthesized images. To solve this problem, a new boundary noise removal algorithm using a preprocessing of the depth map is proposed in this paper. The most common way to eliminate boundary noise caused by boundary misalignment is to modify depth map so that the boundary of the depth map can be matched to that of the reference image. Most conventional methods, however, show poor performances of boundary detection especially in blurred edge, because they are based on a simple boundary search algorithm which exploits signal gradient. In the proposed method, a two-step hierarchical approach for boundary detection is adopted which enables effective boundary detection between the transition and background regions. Experimental results show that the proposed method outperforms conventional ones subjectively and objectively.

Pinpointing of Leakage Location of Water Pipelines using Accelerometers (가속도계를 이용한 상수도 배관의 누수위치 식별연구)

  • 이영섭;윤동진;정중채
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.821-826
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    • 2003
  • Leaks in underground pipelines can cause social, environmental and economical problems. One of a good contermeasures of leaks Is to find and repair of leak points of pipes. Leak noise is a good source to identify the location of leak points of pipelines. Although there have been several methods to detect the leak location with leak noise, such as listening rods, hydrophones or ground microphones, they were not so efficient tools beca. In this paper, two accelermeters are used to detect leak locations which could provide an easier and efficient method. The filtering, signal processing and algorithm is described for the detection of leak location. A 120m-long pipeline system for experiment is installed and the results with the system show that the algorithm with the two accelerometers gives very accurate pinpointing of leaks. Theoretical analysis of sound wave propagation speed in underground pipes is also described.

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Using Mean Shift Algorithm and Self-adaptive Canny Algorithm for I mprovement of Edge Detection (경계선 검출의 향상을 위한 Mean Shift 알고리즘과 자기 적응적 Canny 알고리즘의 활용)

  • Shin, Seong-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.7
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    • pp.33-40
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    • 2009
  • Edge detection is very significant in low level image processing. However, majority edge detection methods are not only effective enough cause of the noise points' influence, even not flexible enough to different input images. In order to sort these problems, in this paper an algorithm is presented that has an extra noise reduction stage at first, and then automatically selects the both thresholds depending on gradient amplitude histogram and intra class minimum variance. Using this algorithm, can fade out almost all of the sensitive noise points, and calculate the propose thresholds for different images without setting up the practical parameters artificially, and then choose edge pixels by fuzzy algorithm. In finally, get the better result than the former Canny algorithm.

A Study on Edge Detection Algorithm using Modified Mask in Salt and Pepper Noise Images (Salt and Pepper 잡음 영상에서 변형된 마스크를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.1
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    • pp.210-216
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    • 2014
  • The edge in the image is a part which the brightness changes rapidly between the object and the object or objects and background, and includes information of the features such as size, position, orientation, and texture of the object. The edge detection is the technique that acquires these information of the images, and now the researches to detect edges are making steady progress. Typical conventional edge detection methods are Sobel, Prewitt, Roberts using the first derivative operator and Laplacian method using the second derivative operator and so on. These methods is more or less insufficient that the characteristics of the edge detection in the image added salt and pepper noise. therefore, in this paper, an edge detection algorithm using modified mask that applies different size mask according to noise density of local mask is proposed.

Noise Whitening-Based Pitch Detection for Speech Highly Corrupted by Colored Noise

  • Byun, Kyung-Jin;Jeong, Sang-Bae;Kim, Hoi-Rin;Hahn, Min-Soo
    • ETRI Journal
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    • v.25 no.1
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    • pp.49-51
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    • 2003
  • Pitch estimation is important in various speech research areas, but when the speech is noisy, accurate pitch estimation with conventional pitch detectors is almost impossible. To solve this problem, we propose a new pitch detection algorithm for noisy speech using a noise whitening technique on the background noise and obtain successful results.

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