• International journal of advanced smart convergence
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• v.8 no.1
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• pp.126-132
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• 2019

Creative thinking appears even before it is expressed in language, and its existence is revealed through emotion, intuition, image and body feeling before logic or linguistics rules work. In this study, Lego is intended to present experimental child interactive content that is applied with a computer vision based on image processing techniques. In the case of infants, the main purpose of this content is the development of hand muscles and the ability to implement imagination. The purpose of the analysis algorithm of the OpenCV library and the image processing using the 'VVVV' that is implemented as a 'Node' in the midst of perceptual changes in image processing technology that are representative of object recognition, and the objective is to use a webcam to film, recognize, derive results that match the analysis and produce interactive content that is completed by the user participating. Research shows what Lego children have made, and children can create things themselves and develop creativity. Furthermore, we expect to be able to infer a diverse and individualistic person's thinking based on more data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.674-679
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• 2006

In this paper a gesture recognition system using 3D feature data is described. The system relies on a novel 3D sensor that generates a dense range mage of the scene. The main novelty of the proposed system, with respect to other 3D gesture recognition techniques, is the capability for robust recognition of complex hand postures such as those encountered in sign language alphabets. This is achieved by explicitly employing 3D hand features. Moreover, the proposed approach does not rely on colour information, and guarantees robust segmentation of the hand under various illumination conditions, and content of the scene. Several novel 3D image analysis algorithms are presented covering the complete processing chain: 3D image acquisition, arm segmentation, hand -forearm segmentation, hand pose estimation, 3D feature extraction, and gesture classification. The proposed system is tested in an application scenario involving the recognition of sign-language postures.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.285-297
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• 2000

One of the research objectives in the area of multimedia human-computer interaction is the application of artificial intelligence and robotics technologies to the development of computer interfaces. This involves utilizing many forms of media, integrating speed input, natural language, graphics, hand pointing gestures, and other methods for interactive dialogues. Although current human-computer communication methods include computer keyboards, mice, and other traditional devices, the two basic ways by which people communicate with each other are voice and gesture. This paper reports on research focusing on the development of an intelligent multimedia interface system modeled based on the manner in which people communicate. This work explores the interaction between humans and computers based only on the processing of speech(Work uttered by the person) and processing of images(hand pointing gestures). The purpose of the interface is to control a pan/tilt camera to point it to a location specified by the user through utterance of words and pointing of the hand, The systems utilizes another stationary camera to capture images of the users hand and a microphone to capture the users words. Upon processing of the images and sounds, the systems responds by pointing the camera. Initially, the interface uses hand pointing to locate the general position which user is referring to and then the interface uses voice command provided by user to fine-the location, and change the zooming of the camera, if requested. The image of the location is captured by the pan/tilt camera and sent to a color TV monitor to be displayed. This type of system has applications in tele-conferencing and other rmote operations, where the system must respond to users command, in a manner similar to how the user would communicate with another person. The advantage of this approach is the elimination of the traditional input devices that the user must utilize in order to control a pan/tillt camera, replacing them with more "natural" means of interaction. A number of experiments were performed to evaluate the interface system with respect to its accuracy, efficiency, reliability, and limitation.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.473-478
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• 2003

In this paper, we propose the gesture recognition system using a motion information from extracted hand region in complex background image. First of all, we measure entropy for the difference image between continuous frames. Using a color information that is similar to a skin color in candidate region which has high value, we extract hand region only from background image. On the extracted hand region, we detect a contour using the chain code and recognize hand gesture by applying improved centroidal profile method. In the experimental results for 6 kinds of hand gesture, unlike existing methods, we can stably recognize hand gesture in complex background and illumination changes without marker. Also, it shows the recognition rate with more than 95% for person and 90∼100% for each gesture at 15 frames/second.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.378-390
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• 2015

Image projectors can turn any surface into a display. Integrating a surface projection with a user interface transforms it into an interactive display with many possible applications. Hand gesture interfaces are often used with projector-camera systems. Hand detection through color image processing is affected by the surrounding environment. The lack of illumination and color details greatly influences the detection process and drops the recognition success rate. In addition, there can be interference from the projection system itself due to image projection. In order to overcome these problems, a gesture interface based on depth images is proposed for projected surfaces. In this paper, a depth camera is used for hand recognition and for effectively extracting the area of the hand from the scene. A hand detection and finger tracking method based on depth images is proposed. Based on the proposed method, a touch interface for the projected surface is implemented and evaluated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.536-539
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• 2002

In this paper, we developed the automatic optical fiber aligner by image processing and automatic loading system. Optical fiber is indispensable for optical communication systems that transmit large volumes of data at high speed, but super-precision technology in sub-micron units is required for optical axis adjustment, we have developed 6-axis micro stage system for I/O optical fiber arrays, the initial automatic aligning system/software for a input optical array by the image processing technique, fast I/O-synchronous aligning strategy, the automatic loading/unloading system and the automatic UV bonding mechanism. In order to adjust the alignment it used on PC based motion controller, a $10\mu\textrm{mm}$ repeat-detailed drawing of automatic loading system is developed by a primary line up for high detailed drawing. Also, at this researches used the image processing system and algorithm instead of the existing a primary hand-line up. and fiber input array and waveguide chip formed in line by automatic. Therefore, the developed and manufactured optical aligning system in this research fulfills the great role of support industry for major electronics manufacturers, telecommunications companies, universities, government agencies and other research institutions.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.241-249
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• 2002

Optical fiber is indispensable for optical communication systems that transmit large volumes of data at high speed, but super precision technology in sub-micron units is required for optical axis adjustment. We developed the automatic optical fiber by image processing and automatic loading system. we have developed 6-axis micro stage system for I/O optical fiber arrays, the initial automatic aligning system software for a input optical array by the image processing technique, fast I/O-synchronous aligning strategy, the automatic loading/unloading system and the automatic UV bonding mechanism. In order to adjust the alignment it used on PC based motion controller, a $10{\mu}m$ repeat-detailed drawing of automatic loading system is developed by a primary line up for high detailed drawing. Also, at this researches used the image processing system and algorithm instead of the existing a primary hand-line up and fiber input array and waveguide chip formed in line by automatic.

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.53-63
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• 2005

We propose a fuzzy neural network (FNN) theory capable of deciding the quality of a road image prior to extracting lane-related information. The accuracy of lane-related information obtained by image processing depends on the quality of the raw images, which can be classified as good or bad according to how visible the lane marks on the images are. Enhancing the accuracy of the information by an image-processing algorithm is limited due to noise corruption which makes image processing difficult. The FNN, on the other hand, decides whether road images are good or bad with respect to the degree of noise corruption. A cumulative distribution function (CDF), a function of edge histogram, is utilized to extract input parameters from the FNN according to the fact that the shape of the CDF is deeply correlated to the road image quality. A suitability analysis shows that this deep correlation exists between the parameters and the image quality. The input pattern vector of the FNN consists of nine parameters in which eight parameters are from the CDF and one is from the intensity distribution of raw images. Experimental results showed that the proposed FNN system was quite successful. We carried out simulations with real images taken in various lighting and weather conditions, and obtained successful decision-making about $99\%$ of the time.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.399-408
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• 2012

Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from hand images. Many methods are available in scientific literature for fingertips detection with an open hand but very poor results are available for fingertips detection when the hand is closed. This paper presents a new method for the detection of fingertips in a closed hand using the corner detection method and an advanced edge detection algorithm. It is important to note that the skin color segmentation methodology did not work for fingertips detection in a closed hand. Thus the proposed method applied Gabor filter techniques for the detection of edges and then applied the corner detection algorithm for the detection of fingertips through the edges. To check the accuracy of the method, this method was tested on a vast number of images taken with a webcam. The method resulted in a higher accuracy rate of detections from the images. The method was further implemented on video for testing its validity on real time image capturing. These closed hand fingertips detection would help in controlling an electro-mechanical robotic hand via hand gesture in a natural way.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.687-688
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• 2023

Bone age assessment is a crucial task in pediatric radiology for assessing growth and development in children. In this paper, we explore the potential of Vision Transformer, a state-of-the-art deep learning model, for bone age assessment using X-ray images. We generate heatmap outputs using a pre-trained Vision Transformer model on a publicly available dataset of hand X-ray images and show that the model tends to focus on the overall hand and only the bone part of the image, indicating its potential for accurately identifying the regions of interest for bone age assessment without the need for pre-processing to remove background noise. We also suggest two methods for extracting the region of interest from the heatmap output. Our study suggests that Vision Transformer holds great potential for bone age assessment using X-ray images, as it can provide accurate and interpretable output that may assist radiologists in identifying potential abnormalities or areas of interest in the X-ray image.