• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.39-48
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• 2005

This paper proposes a novel approach to recognize nine kinds of motion for a multifunction myoelectric hand, acquiring four channel EMG signals from electrodes placed on the forearm. To analyze EMG with properties of nonstationary signal, time-frequency features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. From experimental results, we show that the proposed method enhances the recognition accuracy, and makes it possible to implement a real-time pattern recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1558-1566
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• 1999

While high resolution images are required for various applications, aliased low-resolution images are only available due to the physical limitations of sensors. In this paper, we propose an algorithm to reconstruct a high resolution image from multiple aliased low-resolution images, which is based on the generalized multichannel deconvolution technique. The conventional approaches are based on the discrete Fourier transform (DFT) since the aliasing effect is easily analyzed in the frequency domain. However, the useful solution may not be available in many cases, i.e., the underdetermined cases or the insufficient subpixel information cases. In order to compensate for such ill-posedness, the generalized multichannel regularization was adopted in the spatial domain. Furthermore, the usage of the discrete cosine transform instead of the DFT leads to the computationally efficient reconstruction algorithm. The validity of the proposed algorithm is both theoretically and experimentally demonstrated in this paper. It is also shown that the effect of inaccurate motion information is reduced by regularization.

• Archives of design research
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• v.19 no.2 s.64
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• pp.313-322
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• 2006

In this paper, we introduce 'Contents Based Image Retrieval' which helps a user find the images he or she needs more easily and reconfigures the images automatically. With this system, we try to realize the language of (motion) picture, that is, the Montage from the viewpoint of the user. The Real-time Montage System introduced in this paper uses 'Discrete Fourier Transform'. Through this, the user can find the feature of the image selected and compare the analogousness with the image in the database. This kind of system leads to the user's speedy and effective retrieving, Also, we can acquire the movement image of the user by Camera Tracking in Real-time. The movement image acquired is to be reconfigured automatically with the image of the user. In this way, we can get an easy and speedy image reconfiguration which sets to the user's intention. This system is a New Media Design tool(entertainment) which induces a user enjoy participating in it. In this system, Thus, the user is not just a passive consumer of one-way image channels but an active subject of image reproduction in this system. It is expected to be a foundation for a new style of user-centered movie (media based entertainment).

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.365-371
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• 2018

Uninterrupted monitoring of multiple subjects is required for mass causality events, in hospital environment or for sports by medical technicians or physicians. Movement of subjects under monitoring requires such system to be wireless, sometimes demands multiple transmitters and a receiver as a base station and monitored parameter must not be corrupted by any noise before further diagnosis. A Bluetooth Piconet network is visualized, where each subject carries a Bluetooth transmitter module that acquires vital sign continuously and relays to Bluetooth enabled device where, further signal processing is done. In this paper, a wireless network is realized to capture ECG of two subjects performing different activities like cycling, jogging, staircase climbing at 100 Hz frequency using prototyped Bluetooth module. The paper demonstrates removal of baseline drift using Fast Fourier Transform and Inverse Fast Fourier Transform and removal of high frequency noise using moving average and S-Golay algorithm. Experimental results highlight the efficacy of the proposed work to monitor any vital sign parameters of multiple subjects simultaneously. The importance of removing baseline drift before high frequency noise removal is shown using experimental results. It is possible to use Bluetooth Piconet frame work to capture ECG simultaneously for more than two subjects. For the applications where there will be larger body movement, baseline drift removal is a major concern and hence along with wireless transmission issues, baseline drift removal before high frequency noise removal is necessary for further feature extraction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.19-27
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• 2010

This paper proposes a method for enhancing detection performance and reducing computational cost when detecting a human face by applying B-spline active contour to the frame difference of consecutive images. Firstly, the method estimates amount of user's motion using kurtosis. If the kurtosis is smaller than a pre-defined threshold, it is considered that the amount of user's motion is insufficient and thus the contour fitting is not applied. Otherwise, the contour fitting is applied by exploiting the fact that the amount of motion is sufficient. Secondly, for the contour fitting, difference edges are detected by combining the distance transformation of the binarized frame difference and the edges of current frame. Lastly, the face is located by assigning the contour fitting process to the detected difference edges. Kurtosis-based motion amount estimation can reduce a computational cost and stabilize the results of the contour fitting. In addition, distance transformation-based difference edge detection can enhance the problems of contour lag and discontinuous difference edges. Experimental results confirm that the proposed method can reduce the face localization error caused by the contour lag and discontinuity of edges, and decrease the computational cost by omitting approximately 39% of the contour fitting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.126-133
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• 2003

This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.262-272
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• 2007

SAD (Sum of Absolute Difference) algorithm is the most frequently executing routine in motion estimation, which is the most demanding process in motion picture encoding. To enhance the performance of motion picture encoding on a VLIW processor, an optimal implementation of SAD algorithm on VLIW processor should be accomplished. In this paper, we propose an implementation of optimal scheduling of SAD algorithm with conditional branch on a VLIW-based high performance DSP. We first transform the nested loop with conditional branch of SAD algorithm into a single loop with conditional branch which has a large enough loop body to utilize fully the ILP capability of VLIW DSP and has a conditional branch to make the escape from loop to be achieved as soon as possible. And then we apply a modulo scheduling technique to the transformed single loop. We test the proposed implementation on TMS320C6713, and analyze the code size and performance with respect to processing time. Through experiments, it is shown that the SAD implementation proposed in this paper has small code size appropriate for embedded applications, and the H.263 encoder with the proposed SAD implementation performs better than other H.263 encoder with other SAD implementations.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.42-53
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• 2000

Efficient implementation of pre-filtering has been an important issue in video sequence coding, because it can remove camera noise and improve coding efficiency dramatically This paper introduces a novel pre-filtering scheme that is performed inside a video encoder The proposed pre-filtering is based on the approximated generalized Wiener filtering and two-dimensional discrete cosine transform (DCT) factorization. and is achieved by scaling the DCT coefficients of original image blocks for intra block coding and those of motion-compensated error blocks for inter block coding, respectively Even though the pre-filtering operation is embedded in a video encoder, its additional computational complexity is marginal compared to the encoding process, and the overall architecture of the conventional video encoder is maintained In spite of its simplicity, the proposed pre-filtering scheme provides good filtering and coding performance for noisy video sequences.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.41-52
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• 2009

In Motion JPEG2000 encoding, huge bandwidth requirement of data memory access is the bottleneck in required system performance. For the alleviation of this bandwidth requirement, a new embedded compression(EC) algorithm with a little bit of image quality drop is devised. For both random accessibility and low latency, very simple and efficient entropy coding algorithm is proposed. We achieved significant memory bandwidth reductions (about 53${\sim}$81%) and reduced code-block memory to about half size through proposed multi-mode algorithms, without requiring any modification in JPEG2000 standard algorithm.