• Proceedings of the Optical Society of Korea Conference
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• 1989.02a
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• pp.103-106
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• 1989

A method of adaptive formation of the synthetic discriminant function(SDF) both in image plane and spatial frequency plane by using the Widrow-Hoff learning rule is proposed. The proposed method uses minimum number of interconnections between neurons so it can reduce the time for learning the neural net. Also complex valued interconnection weights are introduced for the purposes of handling the phase objects or Fourier transformed spatial frequency objects which usually have complex values for the representation of not only amplitude but also phase information. Also methods of optical implementation for the complex valued interconnection weights are discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.176-179
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• 2000

The PLL synthesizer is used often in communication system due to several merits, such as broad bandwidth, high accuracy and stability of frequency. But it is difficult to use in current digital communication systems that need frequency hopping at a high speed because of its long frequency hopping time. In this paper, we designed frequency synthesizer that generate the clock frequency randomly at a high speed using the DDS technology and is applied to the pattern generator systemfor for digital image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.443-447
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• 2001

The PLL synthesizer is used often in communication system due to several merits, such as broad bandwidth, high accuracy and stability of frequency. But it is difficult to use in torrent digital communication systems that need frequency hopping at a high speed because of its long frequency hopping time. In this paper, we designed frequency synthesizer that generate the clock frequency randomly at a high speed using the DDS technology and is applied to the pattern generator system for digital image.

• Journal of IKEEE
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• v.20 no.3
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• pp.209-219
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• 2016

SVM is a machine learning method used for image processing. It is well known for its high classification performance. We have to perform multiple MAC operations in order to use SVM for image classification. However, if the resolution of the target image or the number of classification cases increases, the execution time of SVM also increases, which makes it difficult to be performed in real-time applications. In this paper, we propose an hardware architecture which enables real-time applications using SVM classification. We used parallel architecture to simultaneously calculate MAC operations, and also designed the system for several feature extractors for compatibility. RBF kernel was used for hardware implemenation, and the exponent calculation formular included in the kernel was modified to enable fixed point modelling. Experimental results for the system, when implemented in Xilinx ZC-706 evaluation board, show that it can process 60.46 fps for $1360{\times}800$ resolution at 100MHz clock frequency.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.115-125
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• 2019

In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.2
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• pp.224-233
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• 2016

The objective of this study was to develop an artificial neural network (ANN) model for the acoustic identification of commercially important fish species in Korea. A broadband echo acquisition and processing system operating over the frequency range of 85-225 kHz was used to collect and process species-specific, time-frequency feature images from six fish species: black rockfish Sebastes schlegeli, black scraper Thamnaconus modesutus [K], chub mackerel Scomber japonicus, goldeye rockfish Sebastes thompsoni, konoshiro gizzard shad Konosirus punctatus and large yellow croaker Larimichthys crocea. An ANN classifier was developed to identify fish species acoustically on the basis of only 100 dimension time-frequency features extracted by the principal components analysis (PCA). The overall mean identification rate for the six fish species was 88.5%, with individual identification rates of 76.6% for black rockfish, 82.8% for black scraper, 93.8% for chub mackerel, 90.6% for goldeye rockfish, 96.9% for konoshiro gizzard shad and 90.6% for large yellow croaker, respectively. These results demonstrate that individual live fish in well-controlled environments can be identified accurately by the proposed ANN model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.451-454
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• 2005

Recently, many methods to analyze signal have been proposed and representative methods are the Fourier transform and wavelet transform. In these methods, the Fourier transform represents signal with combination cosine and sine at all locations in the frequency domain. However, it doesn't provide time information that particular frequency occurs in signal and depends on only the global feature of the signal. So, to improve these points the wavelet transform which is capable of multiresolution analysis has been applied to many fields such as speech processing, image processing and computer vision. And the wavelet transform, which uses changing window according to scale parameter, presents time-frequency localization. In this paper, we proposed a new approach using a wavelet of cosine and sine type and analyzed features of signal in a limited point of frequency-time plane.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1085-1092
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• 2002

Studies on image information processing have been performed since long time ago because in daily life most of information are acquired by the since of sight. Since there should be a lot of data to describe image as a digital form, data compression is required in order to store or transmit digital image. Lately among most of image compression methods adopted on image compression standards, transform coding methods have been primarily used which transforms the correlations between pixels of image on frequency domain before image compression. It is blown that the standard methods using especially DCT features blocking effect which is the major cause of degrading the quality of image at high compression rate. Fractal encoding using quadtree partition is applied after reducing original image, and we are to find a optimal encoding for the number of scaling bit and offset bit.

• ETRI Journal
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• v.38 no.4
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• pp.599-605
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• 2016

For the implementation of a real-time holographic camera, fast and automatic holographic image reconstruction is an essential technology. In this paper, we propose a new automatic depth-detection algorithm for fast holography reconstruction, which is particularly useful for optical scanning holography. The proposed algorithm is based on the inherent phase difference information in the heterodyne signals, and operates without any additional optical or electrical components. An optical scanning holography setup was created using a heterodyne frequency of 4 MHz with a 500-mm distance and 5-mm depth resolution. The reconstruction processing time was measured to be 0.76 s, showing a 62% time reduction compared to a recent study.

• Journal of IKEEE
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• v.26 no.2
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• pp.226-231
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• 2022

The concept of information entropy has been widely applied in various fields. Recently, in the field of image processing, many technologies applying the concept of information entropy have been developed. As the importance and demand of computer vision technologies increase in modern industry, real-time processing must be possible in order for image processing technologies to be efficiently applied to modern industries. Extracting the entropy value of an image is difficult to process in real-time due to the complexity of computation in software, and a hardware structure of an image entropy filter capable of real-time processing has never been proposed. In this paper, we propose for the first time a hardware structure of a histogram-based entropy filter that can be processed in real time using a barrel shifter. The proposed hardware was designed using Verilog HDL, and Xilinx's xczu7ev-2ffvc1156 was set as the target device and FPGA was implemented. As a result of logic synthesis using the Xilinx Vivado program, it has a maximum operating frequency of 750.751 MHz in a 4K UHD high-resolution environment, and it processes more than 30 images per second and satisfies the real-time processing standard.