• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.72-80
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• 2009

In this parer, we propose a hardware abstraction architecture(HAA) for low cost flash memories that can be applicable to wireless sensor nodes. The proposed HAA consists of three layers. The three layers are 1) HHL(Hardware Interlace Layer), HAL(Hardware Adaption Layer), and HPL(Hardware Presentation Layer), where HIL provides a platform independent interlace to applications of upper layers, HAL performs hardware resource management, program status control, and generation of logical instructions as main core of the HAA, and HPL initializes hardware and communicates data between MCU and flash memory. We implemented our HAA on AT45DB flash memory, and the HAA used 4,384 bytes program memory and 195 bytes data memory respectively. Since the proposed HAA is composed of well defined three layers and shows a low utilization of memory, it can provides a high efficiency in terms of flexibility, scalability, and re-usability, and thus the HAA is well suited for wireless sensor nodes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.414-418
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• 2016

In this paper, a hardware architecture of low area gradient magnitude calculator is proposed. For the hardware complexity reduction, the characteristic of orthogonal projection vector and hardware resource sharing technique are applied. The proposed hardware architecture can be implemented without degradation of the gradient magnitude data quality since the proposed hardware is implemented with original algorithm. The FPGA implementation result shows the 15% of logic elements and 38% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v15.0 environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.141-146
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• 2017

In this paper, a gradient magnitude hardware architecture based on hardware folding design method is proposed for low power image feature extraction. For the hardware complexity reduction, the projection vector chracteristic of gradient magnitude is applied. The proposed hardware architecture can be implemented with the small degradation of the gradient magnitude data quality. The FPGA implementation result shows the 41% of logic elements and 62% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v16.0 environment.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.669-679
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• 2013

This paper proposed a new VLSI (Very Large Scale Integrated Circuit) architecture for stereo matching in real time. We minimized the amount of calculation and the number of memory accesses through analyzing calculation of stereo matching. From this, we proposed a new stereo matching calculating cell and a new hardware architecture by expanding it in parallel, which concurrently calculates cost function for all pixels in a search range. After expanding it, we proposed a new hardware architecture to calculate cost function for 2-dimensional region. The implemented hardware can be operated with minimum 250Mhz clock frequence in FPGA (Field Programmable Gate Array) environment, and has the performance of 805fps in case of the search range of 64 pixels and the image size of $640{\times}480$.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.54-63
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• 2011

This paper proposes a new equation to calculate computer-generated hologram (CGH) in a high speed and its cell-based VLSI (veri large scale integrated circuit) architecture. After finding the calculational regularity in the horizontal or vertical direction from the basic CGH equation, we induce the new equation to calculate the horizontal or vertical hologram pixel values in parallel. We also propose the architecture of the CGH cell consisting of a initial parameter calculator and update-phase calculator(s) on the basis of the equation and implement them in hardware. Also we show a hardware architecture to parallelize the calculation in the horizontal direction by extending CGH. In the experiments we analyze the used hardware resources. These analyses makes it possible to select the amount of hardware to the precision of the results. Here, for the CGH kernel and the structure of the processor, we used the platform from our previous works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.169-177
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• 2015

This paper proposes a hardware architecture for an efficient SAO(Sample Adaptive Offset) with low area for HEVC(High Efficiency Video Coding) encoder. SAO is a newly adopted technique in HEVC as part of the in-loop filter. SAO reduces mean sample distortion by adding offsets to reconstructed samples. The existing SAO requires a great deal of computational and processing time for UHD(Ultra High Definition) video due to sample by sample processing. To reduce SAO processing time, the proposed SAO hardware architecture processes four samples simultaneously, and is implemented with a 2-step pipelined architecture. In addition, to reduce hardware area, it has a single architecture for both luma and chroma components and also uses optimized and common operators. The proposed SAO hardware architecture is designed using Verilog HDL(Hardware Description Language), and has a total of 190k gates in TSMC $0.13{\mu}m$ CMOS standard cell library. At 200MHz, it can support 4K UHD video encoding at 60fps in real time, but operates at a maximum of 250MHz.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.353-356
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• 2002

In this paper, we design an efficient, scalable one-dimensional discrete wavelet transform (1DDWT) filter using data reorder unit (DRU). At each level, the required hardware is optimized by sharing multipliers and adders because the input rate is reduced by a factor of two at each level due to decimation. The proposed architecture shows 100% hardware utilization by balancing hardware with input rate. Furthermore, sharing the coefficients of the highpass and the lowpass filters using the mirror filter property reduces the number of multipliers and adders by half. We designed a scalable DRU that efficiently reorders and feeds inputs to highpass and lowpass filters. The proposed DRU-based architecture is so regular and scalable that it can be easily extended to an arbitrary 1D DWT structure with M taps and J levels. Compared to other architectures, the proposed DWT filter shows efficiency in performance with relatively less hardware.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.3
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• pp.57-63
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• 2005

Kim and Fenn et al. proposed two modular AB multipliers based on LFSR(Linear Feedback Shift Register) architecture. These multipliers use AOP, which has all coefficients with '1', as an irreducible polynomial. Thereby, they have good hardware complexity compared to the previous architectures. This paper proposes a modular $AB^2$ multiplier based on LFSR architecture and a modular exponentiation architecture to improve the hardware complexity of the Kim's. Our multiplier also use the AOP as an irreducible polynomial as the Kim architecture. Simulation result shows that our multiplier reduces the hardware complexity about $50\%$ in the perspective of XOR and AND gates compared to the Kim's. The architecture could be used as a basic block to implement public-key cryptosystems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.192-197
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• 2017

In this paper, image filter optimization method based on common sub-expression elimination is proposed for low-power image feature extraction hardware design. Low power and high performance object recognition hardware is essential for industrial robot which is used for factory automation. However, low area Gaussian gradient filter hardware design is required for object recognition hardware. For the hardware complexity reduction, we adopt the symmetric characteristic of the filter coefficients using the transposed form FIR filter hardware architecture. The proposed hardware architecture can be implemented without degradation of the edge detection data quality since the proposed hardware is implemented with original Gaussian gradient filtering algorithm. The expremental result shows the 50% of multiplier savings compared with previous work.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1183-1190
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• 1999

This paper presents an efficient hardware architecture to improve the frame memory interface occupying the largest hardware area together with motion estimator in implementing MPEG-2 video encoder as an ASIC chip. In this architecture, the memory size for internal data buffering and hardware area for frame memory interface control logic are reduced through the efficient memory map organization of the external SDRAM having dual bank and memory access timing optimization between the video encoder and external SDRAM. In this design, 0.5 m, CMOS, TLM (Triple Layer Metal) standard cells are used as design libraries and VHDL simulator and logic synthesis tools are used for hardware design add verification. The hardware emulator modeled by C-language is exploited for various test vector generation and functional verification. The architecture of the improved frame memory interface occupies about 58% less hardware area than the existing architecture[2-3], and it results in the total hardware area reduction up to 24.3%. Thus, the (act that the frame memory interface influences on the whole area of the video encoder severely is presented as a result.