• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.1-6
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• 2018

In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.354-361
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• 2023

Most of spinal diseases are diagnosed based on the subjective judgment of a specialist, so numerous studies have been conducted to find objectivity by automating the diagnosis process using deep learning. In this paper, we propose a method that combines segmentation and feature extraction, which are frequently used techniques for diagnosing spinal diseases. Four models, U-Net, U-Net++, DeepLabv3+, and M-Net were trained and compared using 1000 X-ray images, and key-points were derived using Douglas-Peucker algorithms. For evaluation, Dice Similarity Coefficient(DSC), Intersection over Union(IoU), precision, recall, and area under precision-recall curve evaluation metrics were used and U-Net++ showed the best performance in all metrics with an average DSC of 0.9724. For the average Euclidean distance between estimated key-points and ground truth, U-Net was the best, followed by U-Net++. However the difference in average distance was about 0.1 pixels, which is not significant. The results suggest that it is possible to extract key-points based on segmentation and that it can be used to accurately diagnose various spinal diseases, including spondylolisthesis, with consistent criteria.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.4
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• pp.62-68
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• 2001

In an early engine development, it is highly required to determine the Key Test Points at the main driving, zone and lessen those points to reduce a test duration. This paper describes that it is possible not only to predict the cycle fuel consumption[g/km], emissions[g/km] from engine data(BSFC[g/kWh], emissions[g/kWh]) but also to confirm the emission regulation potential before a vehicle test.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2512-2529
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• 2015

Wireless mesh networks (WMNs) provide an efficient and flexible method to the field of wireless networking, but also bring many security issues. A mesh point may lose all of its available links during its movement. Thus, the mesh point needs to handover to a new mesh point in order to obtain access to the network again. For multi-domain WMNs, we proposed a new ID-based signcryption scheme and accordingly present a novel ID-based handover protocol for mesh points. The mutual authentication and key establishment of two mesh points which belong to different trust domains can be achieved by using a single one-round message exchange during the authentication phase. The authentication server is not involved in our handover authentication protocol so that mutual authentication can be completed directly by the mesh points. Meanwhile, the data transmitted between the two mesh points can be carried by the authentication messages. Moreover, there are no restrictions on the PKG system parameters in our proposed multi-domain ID-based signcryption scheme so our handover scheme can be easily applied to real WMNs circumstances. Security of the signcryption scheme is proved in the random oracle model. It shows that our protocol satisfies the basic security requirements and is resistant to existing attacks based on the security of the signcryption. The analysis of the performance demonstrates that the protocol is efficient and suitable for the multi-domain WMNs environment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.165-172
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• 2006

In this paper we present a technique for detecting cross-reference points that allows improving watermark detect-ability. In general, Harris detector is commonly used for finding salient points. Harris detector is a kind of combined corner and edge detector which is based on neighboring image data distribution, therefore it has some limitation to find accurate salient points after watermark embedding or any kinds of digital attacks. The new method proposed in this paper used not data distribution but geometrical structure of a normalized image in order to avoid pointing error caused by the distortion of image data. After normalization, we constructed pre-specified number of virtual lines from top to bottom and left to right, and several of cross points were selected by a random key. These selected points specify almost same positions with the accuracy more than that of Harris detector after digital attacks. These points were arranged by a random key, and blocks centered in these points were formed. A reference watermark is formed by a block and embedded in the next block. Because same alteration is applied to the watermark generated and embedded blocks. the detect-ability of watermark is improved even after digital attacks.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.271-275
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• 2003

In this paper, we propose a method that corrects the geometric distortion of mouth in an image. the method is composed of two steps - detecting key points and correcting geometric distortion. First, key points of lips in source and destination images are found by using lips detection algorithm. Then, the two images are mapped by using affine transformation and information found in first step. In experiment result for various mouths with different geometric distortion, we found that the proposed method have satisfactory efficiency.

• Journal of Acupuncture Research
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• v.33 no.4
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• pp.1-6
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• 2016

Objectives : The purpose of this report is to inform readers of the important aspects of about acupuncture and the process of Hwangjenaegyeong Yongchu. Methods : We researched the word 'acupuncture' through Hwangjenaegyeong Youngchu. We formed three categories according to the meanings of the key aspects of acupuncture in each sentence. Results : In Hwangjenaegyeong Youngchu, the meanings of the key aspects of acupuncture (刺鍼之要) are follows : 1. The key aspect of acupuncture(刺鍼之要) is to control Gi & Sin(調氣治神). 2. Before administering acupuncture, a doctor must know Meridian, acu-points, contraindication of nature, Bo-sa acupuncture(補瀉), Deug Gi(得氣), the role of the acupuncture needle(官鍼), the number of the needle, Gi & condition of patients, and pulse diagnosis. 3. For acupuncture, there are several things to be aware of : contraindication of acupuncture, deleteriousness of acupuncture, acu-points, and Bo-sa acupuncture(補瀉).

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.84-92
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• 2002

In this Paper, We propose new performance measure model in Logistic Industry. New model has been learned by key points of PZB model and advanced structure of MBNQA which has cause measure points and effect measure points. The Structure of new performance measure model is Cubic Model which is reflected with time. We try to verify this model apply advance logistic company.

• Journal of Drive and Control
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• v.21 no.2
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• pp.65-71
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• 2024

In this study, we suggested a key-point detection method for robot harvesting of oriental melon. Our suggested method could be used to detect the detachment part and major composition of oriental melon. We defined four points (harvesting point, calyx, center, bottom) based on tomato with characteristics similar to those of oriental melon. The evaluation of estimated key-points was conducted by pixel error and PDK (percentage of detected key-point) index. Results showed that the average pixel error was 18.26 ± 16.62 for the x coordinate and 17.74 ± 18.07 for the y coordinate. Considering the resolution of raw images, these pixel errors were not expected to have a serious impact. The PDK score was found to be 89.5% PDK@0.5 on average. It was possible to estimate oriental melon specific key-point. As a result of this research, we believe that the proposed method can contribute to the application of harvesting robot system.