• 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.

• Transactions on Electrical and Electronic Materials
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• v.18 no.6
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• pp.320-322
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• 2017

In this paper, a high-performance, low-area gradient-magnitude calculator architecture is proposed, based on approximate image processing. To reduce the computational complexity of the gradient-magnitude calculation, vector properties, the symmetry axis, and common terms were applied in a hardware-resource-shared architec-ture. The proposed gradient-magnitude calculator was implemented using an Altera Cyclone IV FPGA (EP4CE115F29) and the Quartus II v.16 device software. It satisfied the output-data quality while reducing the logic elements by 23% and the embedded multipliers by 76%, compared with previous work.

• 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.

• 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.