Based on two-dimensional (2D) bit-embedding/-extraction approach, we propose a simple data hiding for electrocardiogram (ECG) signal. The patient’s sensitive (diagnostic) data can be efficiently hidden into 2D ECG host via the proposed decision rules. The performance of the proposed method using various sizes of the host bundles was demonstrated. Simulations have confirmed that the average SNR of the proposed method with a host bundle of size 3 ´ 3 is superior to that of existing techniques, while our payload is competitive to theirs. In addition, our method with a host bundle of size 2 ´  2 generated the best SNR values, while that with a host bundle of size 4 ´  4 provided the largest payload among the compared methods. Moreover, the proposed method provides robustness performance better than existing ECG steganography. Namely, our method provides high hiding capacity and robust against the attacks such as cropping, inversion, scaling, translation, truncation, and Gaussian noise-addition attacks. Since the proposed method is simple, it can be employed in real-time applications such as portable biometric devices.
Forests in Taiwan contain a diverse variety. Remote sensing data could offer information of large area sampling, but it is very challenging to automatically detect tree and delineate three crown in remote sensing data. Recently a algorithm, called multi-level morphological active contour algorithm (MMAC), has been proposed to address these issues in [1]. It combines a multi-level morphological approach with the active contour model. However, this algorithm comes with a price, which is huge computational complexity, to prevent it from being implemented practically in medium-or largescale images. This manuscript aimed to accelerate MMAC by developing a parallel processing approach using reconfigurable computing platform with field-programmable gate arrays (FPGA). The experimental evaluation indicated that the proposed architecture could provide around 40% acceleration with simple implementation in hardware.Index Terms-Morphological active contour algorithm (MMAC); parallel processing; field programmable gate arrays (FPGA)
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