• Title/Summary/Keyword: Blind Step

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3D Detection of Obstacle Distribution and Mapping for Walking Guide of the Blind (시각 장애인 보행안내를 위한 장애물 분포의 3차원 검출 및 맵핑)

  • Yoon, Myoung-Jong;Jeong, Gu-Young;Yu, Kee-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.2
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    • pp.155-162
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    • 2009
  • In walking guide robot, a guide vehicle detects an obstacle distribution in the walking space using range sensors, and generates a 3D grid map to map the obstacle information and the tactile display. And the obstacle information is transferred to a blind pedestrian using tactile feedback. Based on the obstacle information a user plans a walking route and controls the guide vehicle. The algorithm for 3D detection of an obstacle distribution and the method of mapping the generated obstacle map and the tactile display device are proposed in this paper. The experiment for the 3D detection of an obstacle distribution using ultrasonic sensors is performed and estimated. The experimental system consisted of ultrasonic sensors and control system. In the experiment, the detection of fixed obstacles on the ground, the moving obstacle, and the detection of down-step are performed. The performance for the 3D detection of an obstacle distribution and space mapping is verified through the experiment.

The Expectation and Sparse Maximization Algorithm

  • Barembruch, Steffen;Scaglione, Anna;Moulines, Eric
    • Journal of Communications and Networks
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    • v.12 no.4
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    • pp.317-329
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    • 2010
  • In recent years, many sparse estimation methods, also known as compressed sensing, have been developed. However, most of these methods presume that the measurement matrix is completely known. We develop a new blind maximum likelihood method-the expectation-sparse-maximization (ESpaM) algorithm-for models where the measurement matrix is the product of one unknown and one known matrix. This method is a variant of the expectation-maximization algorithm to deal with the resulting problem that the maximization step is no longer unique. The ESpaM algorithm is justified theoretically. We present as well numerical results for two concrete examples of blind channel identification in digital communications, a doubly-selective channel model and linear time invariant sparse channel model.

Implementation of DSP Embedded Number-Braille Conversion Algorithm based on Image Processing (DSP 임베디드 숫자-점자 변환 영상처리 알고리즘의 구현)

  • Chae, Jin-Young;Darshana, Panamulle Arachchige Udara;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.11 no.2
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    • pp.14-17
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    • 2016
  • This paper describes the implementation of automatic number-braille converter based on image processing for the blind people. The algorithm is consists of four main steps. First step is binary image conversion of the input image obtained by the camera. the second step is segmentation operation by means of dilation and labelling of the character. Next step is calculation of cross-correlation between segmented text image and pre-defined text-pattern image. The final step is generation of brail output which is relevant to input image. The computer simulation result was showing 91.8% correct conversion rate for arabian numbers which is printed in A4-sheet and practical possibility was also confirmed by using implemented automatic number-braille converter based on DSP image processing board.

The effect of gait training with an elastic ankle-foot orthosis on balance and walking ability of persons with chronic stroke: a randomized controlled trial

  • Chi, Ming Hao;Yim, Jong Eun;Yi, Dong hyun
    • Physical Therapy Rehabilitation Science
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    • v.9 no.4
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    • pp.222-229
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    • 2020
  • Objective: The purpose of this study was to investigate the effect of treadmill exercise on the posture and walking speed of chronic stroke survivors with an ankle-foot orthosis. Design: Randomized controlled trial. Methods: Twenty-four chronic persons with chronic stroke admitted to Bobath Memorial Hospital in Seongnam city were divided into two groups by random blind method. Treadmill exercise with an elastic ankle-foot orthosis was performed in the experimental group and treadmill exercise was performed in the control group. The experiment was carried out for 6 weeks, and the experiment was carried out three times a week for 20 minutes per session. To measure the effect, static balance was measured using the MTD system before and after training, and the Berg Balance Scale (BBS) was used to measure functional balance. Results: There was a statistically significant difference between the 2 groups in the BBS measurement results for confirming the functional balance (p<0.05). Also, there was a significant difference between the 2 groups in single limb support time, step time and step length (p<0.05). Conclusions: In this study, it was found that treadmill exercise with an elastic ankle-foot orthosis in persons with chronic stroke was effective in maintaining functional balance, walking ability, step length, and step time. Therefore, it is necessary to use a flexible ankle-foot orthosis with proper treadmill exercise as a method of improving balance and walking speed of chronic stroke survivors.

Comparison for the variable step-size FDICA with BSS algorithm in reverberant condition (반향환경에서의 가변 적응 상수를 이용한 FDICA와 여러 BSS 알고리즘과의 비교)

  • Park Keun-Soo;Park Jang-Sik;Son Kyung-Sik
    • Proceedings of the Korea Contents Association Conference
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    • 2005.05a
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    • pp.369-373
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    • 2005
  • This paper proposes a variable step size parameter method in frequency domain ICA (FDICA). The FDICA and the temporal analysis (TA) algorithm are experimented for blind source separation (BSS). This paper will compare the separation qualities of these two algorithms in various reverberation environments. Furthermore, it is shown that the proposed technique has the better separation performance than those of two methods especially in recorded data.

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Audio Watermarking Using Quantization Index Modulation on Significant Peaks in Frequency Domain (주파수 영역에서 주요 피크에 QIM을 적용한 오디오 워터마킹)

  • Kang, Jung-Sun;Cho, Sang-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.6
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    • pp.303-307
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    • 2011
  • This paper describes an audio watermarking using Quantization Index Modulation (QIM) on significant peaks in frequency domain. The audio signal is broken up into L samples length frames with non-overlapping and rectangular window. The zero-crossing rate of each frame is calculated for decision whether it is proper to be watermarked or not. If the frame is legitimate, frequency magnitude response is computed by discrete Fourier transform. For the QIM, we set the quantization step size based on maximum value of frequency magnitude response and select n significant peaks with w samples around them in frequency domain, totally $n{\times}(w+1)$ samples. Finally, watermark embedding is performed. Decoder extract watermarks based on Euclidean distance, that is a blind detection. The proposed method is robust against many attacks of watermark benchmark.

A Blind Watermarking Algorithm of 3D Mesh Model for Rapid Prototyping System Application (RP 시스템 적용을 위한 3차원 메쉬 모델의 블라인드 워터마킹)

  • Ji-Zhe, Cui
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.12C
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    • pp.1194-1202
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    • 2007
  • In this paper, we proposed a blind watermarking algorithm to apply to the rapid prototyping system. The 3D mesh model is used in the step of the CAD modeling before the making of the prototype system of the rapid prototyping system. STL type mesh modeling which is used in this system reduces the error of the system and improves the accuracy of the system. In the step of the CAD modeling, some transformations which do not change the model accuracy are used, but some transformations which change the model accuracy are not used because the mesh model error is related to the accuracy of the prototype system. Most watermarking algorithms embedded a specific random noise as the watermark information into the model. These kinds of the algorithms are not proper to the 3D model watermarking. The proposed algorithm can be used for the accurate prototyping system because it does not change the model after the watermark embedding This means it can be used for the copyright marking and the data integrity.

Traffic Signal Recognition System Based on Color and Time for Visually Impaired

  • P. Kamakshi
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.48-54
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    • 2023
  • Nowadays, a blind man finds it very difficult to cross the roads. They should be very vigilant with every step they take. To resolve this problem, Convolutional Neural Networks(CNN) is a best method to analyse the data and automate the model without intervention of human being. In this work, a traffic signal recognition system is designed using CNN for the visually impaired. To provide a safe walking environment, a voice message is given according to light state and timer state at that instance. The developed model consists of two phases, in the first phase the CNN model is trained to classify different images captured from traffic signals. Common Objects in Context (COCO) labelled dataset is used, which includes images of different classes like traffic lights, bicycles, cars etc. The traffic light object will be detected using this labelled dataset with help of object detection model. The CNN model detects the color of the traffic light and timer displayed on the traffic image. In the second phase, from the detected color of the light and timer value a text message is generated and sent to the text-to-speech conversion model to make voice guidance for the blind person. The developed traffic light recognition model recognizes traffic light color and countdown timer displayed on the signal for safe signal crossing. The countdown timer displayed on the signal was not considered in existing models which is very useful. The proposed model has given accurate results in different scenarios when compared to other models.

Multi-Constant Modulus Algorithm for Blind Decision Feedback Equalizer (블라인드 결정 궤환 등화기를 위한 다중 계수 알고리즘)

  • Kim, Jung-Su;Chong, Jong-Wha
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.6
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    • pp.709-717
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    • 2002
  • A new multi constant modulus algorithm (MCMA) for a blind decision feedback equalizer is proposed. In order to avoid the error propagation problem in the conventional DFE structure, Feed-Back Filter coefficients are updated only after Feed-Forward Filter coefficients are sufficiently converged to the steady state. Therefore, it has the problem of slow convergence speed characteristics. To overcome this drawback, the proposed MCMA algorithm uses not only new cost function considering the minimum distance between the received signal and the representative value containing the statistical characteristics of the transmitted signal, but also adaptive step-size according to the equalizer outputs to fast convergence speed of FBF. Simulations were carried out under the certified communication channel environment to evaluate a performance of the proposed equalizer. The simulation results show that the proposed equalizer has an improved convergence and SER performance compared with previous methods. The proposed techniques offer the possibility of practical equalization for cable modem and terrestrial HDTV broadcast (using 8-VSB or 64-QAM) applications.

Underdetermined Blind Source Separation from Time-delayed Mixtures Based on Prior Information Exploitation

  • Zhang, Liangjun;Yang, Jie;Guo, Zhiqiang;Zhou, Yanwei
    • Journal of Electrical Engineering and Technology
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    • v.10 no.5
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    • pp.2179-2188
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    • 2015
  • Recently, many researches have been done to solve the challenging problem of Blind Source Separation (BSS) problems in the underdetermined cases, and the “Two-step” method is widely used, which estimates the mixing matrix first and then extracts the sources. To estimate the mixing matrix, conventional algorithms such as Single-Source-Points (SSPs) detection only exploits the sparsity of original signals. This paper proposes a new underdetermined mixing matrix estimation method for time-delayed mixtures based on the receiver prior exploitation. The prior information is extracted from the specific structure of the complex-valued mixing matrix, which is used to derive a special criterion to determine the SSPs. Moreover, after selecting the SSPs, Agglomerative Hierarchical Clustering (AHC) is used to automaticly cluster, suppress, and estimate all the elements of mixing matrix. Finally, a convex-model based subspace method is applied for signal separation. Simulation results show that the proposed algorithm can estimate the mixing matrix and extract the original source signals with higher accuracy especially in low SNR environments, and does not need the number of sources before hand, which is more reliable in the real non-cooperative environment.