• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.4
• /
• pp.1-9
• /
• 2023

In this paper, we propose a method to recognize the braille blocks for embedded devices in real time through deep learning. First, a deep learning model for braille block recognition is trained on a high-performance computer, and the learning model is applied to a lightweight tool to apply to an embedded device. To recognize the walking information of the braille block, an algorithm is used to determine the path using the distance from the braille block in the image. After detecting braille blocks, bollards, and crosswalks through the YOLOv8 model in the video captured by the embedded device, the walking information is recognized through the braille block path discrimination algorithm. We apply the model lightweight tool to YOLOv8 to detect braille blocks in real time. The precision of YOLOv8 model weights is lowered from the existing 32 bits to 8 bits, and the model is optimized by applying the TensorRT optimization engine. As the result of comparing the lightweight model through the proposed method with the existing model, the path recognition accuracy is 99.05%, which is almost the same as the existing model, but the recognition speed is reduced by 59% compared to the existing model, processing about 15 frames per second.

• The Korean Journal of Nuclear Medicine
• /
• v.39 no.6
• /
• pp.413-420
• /
• 2005

Purpose: Neuroreceptor PET studies require 60-120 minutes to complete and head motion of the subject during the PET scan increases the uncertainty in measured activity. In this study, we investigated the effects of the data-driven head mutton correction on the evaluation of endogenous dopamine release (DAR) in the striatum during the motor task which might have caused significant head motion artifact. Materials and Methods: $[^{11}C]raclopride$ PET scans on 4 normal volunteers acquired with bolus plus constant infusion protocol were retrospectively analyzed. Following the 50 min resting period, the participants played a video game with a monetary reward for 40 min. Dynamic frames acquired during the equilibrium condition (pre-task: 30-50 min, task: 70-90 min, post-task: 110-120 min) were realigned to the first frame in pre-task condition. Intra-condition registrations between the frames were performed, and average image for each condition was created and registered to the pre-task image (inter-condition registration). Pre-task PET image was then co-registered to own MRI of each participant and transformation parameters were reapplied to the others. Volumes of interest (VOI) for dorsal putamen (PU) and caudate (CA), ventral striatum (VS), and cerebellum were defined on the MRI. Binding potential (BP) was measured and DAR was calculated as the percent change of BP during and after the task. SPM analyses on the BP parametric images were also performed to explore the regional difference in the effects of head motion on BP and DAR estimation. Results: Changes in position and orientation of the striatum during the PET scans were observed before the head motion correction. BP values at pre-task condition were not changed significantly after the intra-condition registration. However, the BP values during and after the task and DAR were significantly changed after the correction. SPM analysis also showed that the extent and significance of the BP differences were significantly changed by the head motion correction and such changes were prominent in periphery of the striatum. Conclusion: The results suggest that misalignment of MRI-based VOI and the striatum in PET images and incorrect DAR estimation due to the head motion during the PET activation study were significant, but could be remedied by the data-driven head motion correction.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.6
• /
• pp.6-15
• /
• 2009

In this paper, a new 4-way search window is designed for the high-performance 2D PE architecture in H.264 Motion Estimation(ME) to improve the memory bandwidth. While existing 2D PE architectures reuse the overlapped data of adjacent search windows scanned in 1 or 3-way, the new window utilizes the overlapped data of adjacent search windows as well as adjacent multiple scanning (window) paths to enhance the reusage of retrieved search window data. In order to scan adjacent windows and multiple paths instead of single raster and zigzag scanning of adjacent windows, bidirectional row and column window scanning results in the 4-way(up. down, left, right) search window. The proposed 4-way search window could improve the reuse of overlapped window data to reduce the redundancy access factor by 3.1, though the 1/3-way search window redundantly requires $7.7{\sim}11$ times of data retrieval. Thus, the new 4-way search window scheme enhances the memory bandwidth by $70{\sim}58%$ compared with 1/3-way search window. The 2D PE architecture in H.264 ME for 4-way search window consists of $16{\times}16$ pe array. computing the absolute difference between current and reference frames, and $5{\times}16$ reusage array, storing the overlapped data of adjacent search windows and multiple scanning paths. The reference data could be loaded upward and downward into the new 2D PE depending on scanning direction, and the reusage array is combined with the pe array rotating left as well as right to utilize the overlapped data of adjacent multiple scan paths. In experiments, the new implementation of 4-way search window on Magnachip 0.18um could deal with the HD($1280{\times}720$) video of 1 reference frame, $48{\times}48$ search area and $16{\times}16$ macroblock by 30fps at 149.25MHz.

• Journal of Korea Water Resources Association
• /
• v.56 no.6
• /
• pp.403-417
• /
• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Progress in Medical Physics
• /
• v.23 no.2
• /
• pp.91-98
• /
• 2012

Verification of internal organ motion during treatment and its feedback is essential to accurate dose delivery to the moving target. We developed an offline based internal organ motion verification system (IMVS) using cine EPID images and evaluated its accuracy and availability through phantom study. For verification of organ motion using live cine EPID images, a pattern matching algorithm using an internal surrogate, which is very distinguishable and represents organ motion in the treatment field, like diaphragm, was employed in the self-developed analysis software. For the system performance test, we developed a linear motion phantom, which consists of a human body shaped phantom with a fake tumor in the lung, linear motion cart, and control software. The phantom was operated with a motion of 2 cm at 4 sec per cycle and cine EPID images were obtained at a rate of 3.3 and 6.6 frames per sec (2 MU/frame) with $1,024{\times}768$ pixel counts in a linear accelerator (10 MVX). Organ motion of the target was tracked using self-developed analysis software. Results were compared with planned data of the motion phantom and data from the video image based tracking system (RPM, Varian, USA) using an external surrogate in order to evaluate its accuracy. For quantitative analysis, we analyzed correlation between two data sets in terms of average cycle (peak to peak), amplitude, and pattern (RMS, root mean square) of motion. Averages for the cycle of motion from IMVS and RPM system were $3.98{\pm}0.11$ (IMVS 3.3 fps), $4.005{\pm}0.001$ (IMVS 6.6 fps), and $3.95{\pm}0.02$ (RPM), respectively, and showed good agreement on real value (4 sec/cycle). Average of the amplitude of motion tracked by our system showed $1.85{\pm}0.02$ cm (3.3 fps) and $1.94{\pm}0.02$ cm (6.6 fps) as showed a slightly different value, 0.15 (7.5% error) and 0.06 (3% error) cm, respectively, compared with the actual value (2 cm), due to time resolution for image acquisition. In analysis of pattern of motion, the value of the RMS from the cine EPID image in 3.3 fps (0.1044) grew slightly compared with data from 6.6 fps (0.0480). The organ motion verification system using sequential cine EPID images with an internal surrogate showed good representation of its motion within 3% error in a preliminary phantom study. The system can be implemented for clinical purposes, which include organ motion verification during treatment, compared with 4D treatment planning data, and its feedback for accurate dose delivery to the moving target.