• Title/Summary/Keyword: automatic enhancement

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Image Enhancement using Automatic Unsharp Masking (Automatic Unsharp masking을 이용한 영상 개선)

  • Park, Hyun-Jun;Kim, Mi-Kyung;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.985-988
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    • 2007
  • This paper presents techniques to make image enhancement using unsharp masking. It is the technique to make image enhancement by automatically find the three parameters that makes hard to use the unsharp mask technique. To optimize the three parameters(Threshold, Amount, Radius), at first classify the pixels in the image to three groups, and then according to the groups, apply the unsharp mask to the image differently. We experimented and analyzed the rate of image enhancement by comparing images which is enhanced by human and which is enhanced by proposed technique.

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Performance Analysis of a Class of Single Channel Speech Enhancement Algorithms for Automatic Speech Recognition (자동 음성 인식기를 위한 단채널 음질 향상 알고리즘의 성능 분석)

  • Song, Myung-Suk;Lee, Chang-Heon;Lee, Seok-Pil;Kang, Hong-Goo
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.2E
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    • pp.86-99
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    • 2010
  • This paper analyzes the performance of various single channel speech enhancement algorithms when they are applied to automatic speech recognition (ASR) systems as a preprocessor. The functional modules of speech enhancement systems are first divided into four major modules such as a gain estimator, a noise power spectrum estimator, a priori signal to noise ratio (SNR) estimator, and a speech absence probability (SAP) estimator. We investigate the relationship between speech recognition accuracy and the roles of each module. Simulation results show that the Wiener filter outperforms other gain functions such as minimum mean square error-short time spectral amplitude (MMSE-STSA) and minimum mean square error-log spectral amplitude (MMSE-LSA) estimators when a perfect noise estimator is applied. When the performance of the noise estimator degrades, however, MMSE methods including the decision directed module to estimate a priori SNR and the SAP estimation module helps to improve the performance of the enhancement algorithm for speech recognition systems.

Implementation of Chip and Algorithm of a Speech Enhancement for an Automatic Speech Recognition Applied to Telematics Device (텔레메틱스 단말용 음성 인식을 위한 음성향상 알고리듬 및 칩 구현)

  • Kim, Hyoung-Gook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.7 no.5
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    • pp.90-96
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    • 2008
  • This paper presents an algorithm of a single chip acoustic speech enhancement for telematics device. The algorithm consists of two stages, i.e. noise reduction and echo cancellation. An adaptive filter based on cross spectral estimation is used to cancel echo. The external background noise is eliminated and the clear speech is estimated by using MMSE log-spectral magnitude estimation. To be suitable for use in consumer electronics, we also design a low cost, high speed and flexible hardware architecture. The performance of the proposed speech enhancement algorithms were measured both by the signal-to-noise ratio(SNR) and recognition accuracy of an automatic speech recognition(ASR) and yields better results compared with the conventional methods.

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Adaptive Enhancement Method for Robot Sequence Motion Images

  • Yu Zhang;Guan Yang
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.370-376
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    • 2023
  • Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

An automatic detection method for lung nodules based on multi-scale enhancement filters and 3D shape features

  • Hao, Rui;Qiang, Yan;Liao, Xiaolei;Yan, Xiaofei;Ji, Guohua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.347-370
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    • 2019
  • In the computer-aided detection (CAD) system of pulmonary nodules, a high false positive rate is common because the density and the computed tomography (CT) values of the vessel and the nodule in the CT images are similar, which affects the detection accuracy of pulmonary nodules. In this paper, a method of automatic detection of pulmonary nodules based on multi-scale enhancement filters and 3D shape features is proposed. The method uses an iterative threshold and a region growing algorithm to segment lung parenchyma. Two types of multi-scale enhancement filters are constructed to enhance the images of nodules and blood vessels in 3D lung images, and most of the blood vessel images in the nodular images are removed to obtain a suspected nodule image. An 18 neighborhood region growing algorithm is then used to extract the lung nodules. A new pulmonary nodules feature descriptor is proposed, and the features of the suspected nodules are extracted. A support vector machine (SVM) classifier is used to classify the pulmonary nodules. The experimental results show that our method can effectively detect pulmonary nodules and reduce false positive rates, and the feature descriptor proposed in this paper is valid which can be used to distinguish between nodules and blood vessels.

Evaluation of Structural Design Enhancement and Sensitivity of Automatic Ocean Salt Collector According to Design of Experiments

  • Song, Chang Yong;Lee, Dong-Jun;Lee, Jin Sun;Kim, Eun Mi;Choi, Bo-Youp
    • Journal of Ocean Engineering and Technology
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    • v.34 no.4
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    • pp.253-262
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    • 2020
  • This study provides a comparative analysis of experiments-based enhancements and sensitivity evaluations for the structural design of an automatic ocean salt collector under various load conditions. The sizing variables of the structural members were considered as design factors. The strength and weight performances were selected as output responses. The design of experiments used in the comparative study consisted of the orthogonal array design, Box-Behnken design, and central composite design. The response surface model, one of the metamodels, was applied to the approximate model generation. The design enhancement performance metrics, including numerical costs and weight minimization, according to the design of experiments, were compared from the best design case results. The central composite design method showed the most enhanced design results for the structural design of the automatic ocean salt collector.

An Effective Retinal Vessel and Landmark Detection Algorithm in RGB images

  • Jung Eun-Hwa
    • International Journal of Contents
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    • v.2 no.3
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    • pp.27-32
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    • 2006
  • We present an effective algorithm for automatic tracing of retinal vessel structure and vascular landmark extraction of bifurcations and ending points. In this paper we deal with vascular patterns from RGB images for personal identification. Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing in RGB images has many problems which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting vascular structure using eight directional information, and extracting retinal vascular structure, and Vascular Landmark Extraction by extracting bifurcations and ending points. The results of automatic retinal vessel extraction using jive different thresholds applied 34 eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only robust and accurate vessel tracing but also vascular landmarks according to thresholds.

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Speech Estimators Based on Generalized Gamma Distribution and Spectral Gain Floor Applied to an Automatic Speech Recognition (잡음에 강인한 음성인식을 위한 Generalized Gamma 분포기반과 Spectral Gain Floor를 결합한 음성향상기법)

  • Kim, Hyoung-Gook;Shin, Dong;Lee, Jin-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.3
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    • pp.64-70
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    • 2009
  • This paper presents a speech enhancement technique based on generalized Gamma distribution in order to obtain robust speech recognition performance. For robust speech enhancement, the noise estimation based on a spectral noise floor controled recursive averaging spectral values is applied to speech estimation under the generalized Gamma distribution and spectral gain floor. The proposed speech enhancement technique is based on spectral component, spectral amplitude, and log spectral amplitude. The performance of three different methods is measured by recognition accuracy of automatic speech recognition (ASR).

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Automatic Threshold Selection and Contrast Intensification Technique for Image Enhancement (영상 향상을 위한 자동 임계점 선택 및 대비 강화 기법)

  • Lee, Geum-Boon;Cho, Beom-Joon
    • Journal of Korea Multimedia Society
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    • v.11 no.4
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    • pp.462-470
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    • 2008
  • This study applies fuzzy functions to improve image quality under the assumption that uncertainty of image information due to low contrast is based on vagueness and ambiguity of the brightness pixel values. To solve the problem of low contrast images whose brightness distribution is inclined, we use the k-means algorithm as a parameter of the fuzzy function, through which automatic critical points can be found to differentiate objects from background and contrast between bright and dark points can be improved. The fuzzy function is presented at the three main stages presented to improve image quality: fuzzification, contrast enhancement and defuzzification. To measure improved image quality, we present the fuzzy index and entropy index and in comparison with those of histogram equalization technique, it shows outstanding performance.

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A Real-Time Histogram Equalization System with Automatic Gain Control Using FPGA

  • Cho, Jung-Uk;Jin, Seung-Hun;Kwon, Key-Ho;Jeon, Jae-Wook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.4
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    • pp.633-654
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    • 2010
  • High quality camera images, with good contrast and intensity, are needed to obtain the desired information. Images need to be enhanced when they are dark or bright. The histogram equalization technique, which flattens the density distribution of an image, has been widely used to enhance image contrast due to its effectiveness and simplicity. This technique, however, cannot be used to enhance images that are either too dark or too bright. In addition, it is difficult to perform histogram equalization in real-time using a general-purpose computer. This paper proposes a histogram equalization technique with AGC (Automatic Gain Control) to extend the image enhancement range. It is designed using VHDL (VHSIC Hardware Description Language) to enhance images in real-time. The system is implemented with an FPGA (Field Programmable Gate Array). An image processing system with this FPGA is implemented. The performance of this image processing system is measured.