The in-line holography has obvious advantages especially in wider spatial bandwidth over the off-axis holography. However, a direct current(DC)-noise and an unwanted twin image should be separated or eliminated in the in-line holography for a high quality reconstruction. An approach for suppressing the twin image is proposed by separating the real and twin image regions in the digital holography. Specifically, the initial region of real and twin images is obtained by a blind separation matrix, and the segmentation mask to suppress the twin image is calculated by nonlinear quantization from the segmented image. For the performance evaluation, the proposed method is compared with the existing approaches including the overlapping block variance and manual-based schemes. Experimental results showed that the proposed method has a better performance at the overlapped region of the real and twin images. Additionally, the proposed method causes less loss of real image than the overlapping block variance-based scheme. Therefore, we believe that the proposed scheme can be a useful tool for high quality reconstruction in the in-line holography.
[Purpose] This study was performed to provide evidence for the therapeutic exercise
approach through a compative analysis of muscle activities according to climbing wall
inclination. [Subjects and Methods] Twentyfour healthy adult subjects without climbing
experience performed static exercises at a therapeutic climbing at with various
inclination angles (0°, 10°, 20°), and the activities of the trunk muscles (rectus
abdominis, obliquus externus abdominis, obliquus internus abdominis, erector spinae) were
measured using surface electromyography (EMG) for 7 seconds. [Results] Significant
differences were found between the inclination angles of 10° and 0°, as well as 20° in the
rectus abdominis, obliquus internus abdominis, right obliquus externus abdominis, and
right erector spinae. [Conclusion] Based on measurements of trunk muscle activity in a
static climbing standing position at different angles, significant changes in muscle
activity appear to be induced at 10 degrees. Therefore, the results appear to provide
clinically relevant evidence.
Among the image features for object recognition, speeded up robust features (SURF) have been widely implemented due to their hardware-friendly characteristics and high accuracy. However, because of adopting a fully internal memory-based architecture and a field programmable gate array having large memories for a high performance, most of them are infeasible to the application specific integrated chip (ASIC). A memory-efficient architecture for implementing SURF in ASIC by analysing the characteristics of memory accesses of SURF is presented. In addition, a strategy of dividing an entire image into multiple sub-images, processing them sequentially and overlapping each other to reduce the size of the internal memory while minimising the loss of information is proposed. The proposed architecture was implemented with 767 kb-sized internal memories and 1.2 M logic gates while processing 60 frames per second.
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