• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.125-133
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• 2008

Motion blur is a blurring effect on an image caused by the relative motion between the camera and objects in the scene. When an image is captured, motion blurs are caused by relative motion between the camera and the scene. When different objects are moving at different speeds, the characteristics of the blur effect for each object appear differently. To restore the spatially variant blurred image, each of the blur extents should be identified. In this paper, we propose a new method for the identification of blur extent locally using RATS from the image in which the spatially variant motion blur is caused Experiment shows that the proposed algorithm successfully segments the objects with different blurs and identifies the blur extents quite well.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.35-41
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• 2017

We propose a face recognition and notification system that can transform visual face information into tactile signals in order to help visually impaired people. The proposed system consists of a glasses type camera, a mobile computer and an electronic cane. The glasses type camera captures the frontal view of the user, and sends this image to mobile computer. The mobile computer starts to search for human's face in the image when obstacles are detected by ultrasonic sensors. In a case that human's face is detected, the mobile computer identifies detected face. At this time, Adaboost and compressive sensing are used as a detector and a classifier, respectively. After the identification procedures of the detected face, the identified face information is sent to controller attached to a cane using a Bluetooth communication. The controller generates motor control signals using Pulse Width Modulation (PWM) according to the recognized face labels. The vibration motor generates vibration patterns to inform the visually impaired person of the face recognition result. The experimental results of face recognition and notification system show that proposed system is helpful for visually impaired people by providing person identification results in front of him/her.

• Journal of information and communication convergence engineering
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• v.22 no.2
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• pp.109-120
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• 2024

Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature, human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcing strict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. Artificial Intelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as an excellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paper proposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the training dataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrect location and sends an alert notice to the relevant authority.

• Journal of the Ergonomics Society of Korea
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• v.24 no.2
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• pp.35-43
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• 2005

The purpose of this study is to suggest computer assisted neck-base's landmark identification algorithms and measurement extraction methods from three-dimensional human scan data. So we developed the algorithms for automatic identification of landmarks related to the neck-base types. The subjects were 58 women $18{\sim}24$ years of age. Their body were measured directly and indirectly by using camera and three-dimensional body scanner. They were measured during the months of October in 2001. Based on the characters of classified neck-base types, algorithms for the automatic identification of landmarks and methods of automatic measurement are developed. The three-dimensional automatic measuring program is made by $C^{++}$ language. Using this program, 4 landmarks are identified and 6 items are measured. In the verifying the precision of automatic measurement, the height measurements(cervicale, side neck point, front neck point) were relatively accurate, but neck-base width measurement was measured wide.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.10
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• pp.595-603
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• 2005

This Paper proposes the tire mold number identification method which reads the letters on a tire surface with 3D. It is very difficult to separate the letters from the background of an image since the letters on a tire surface is an embossed data. There was many studies to read the letters on a tire surface for the factory automation, however, it was very difficult to separate the letters from the background of an image since the letters on a tire surface is embossed black characters on the black ground. In this study, we first developed the method to find the location of tire mold number, which is used to classify the tire size, from the embossed letters on a tire surface using 3-dimensional laser profile camera which is not affected by the lighting condition, then developed the method to separate the mold number from that location. As a result, we were able to contribute to automate the tire size classification which has been manually performed by operators previously.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.289-292
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• 2007

An object color identification and classification embedded system realization for uninhabited stock management is presented in this paper. The embedded system is realized by using ultrasonic sensor to extract the object and distance, and detecting binary image from USB CCD camera. The algorithm is identified by comparing the reference pattern with the color pattern of input image, and move to the settled rack at the store. The experimental result leads to use the uninhibited stock management with practice as a robot.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2153-2158
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• 2016

Multimedia such as image, audio, and video is easy to create and distribute with the advance of IT. Since novice uses them for illegal purposes, multimedia forensics are required to protect contents and block illegal usage. This paper presents a multimedia forensic algorithm for video to identify the device used for acquiring unknown video files. First, the way to calculate a sensor pattern noise using Wiener filter (W-SPN) is presented, which comes from the imperfection of photon detectors against light. Then, the way to identify the device is explained after estimating W-SPNs from the reference device and the unknown video. For the experiment, 30 devices including DSLR, compact camera, smartphone, and camcorder are tested and analyzed quantitatively. Based on the results, the presented algorithm can achieve the 96.0% identification accuracy.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2891-2894
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• 1999

This paper proposes an alternative personal identification algorithm using finger crease pattern which is assumed to overcome the disadvantages of the existing biometrics system. We used a CED camera with LED lighting as the input device. The original images were treated by employing a lowpass and highpass Jilter to get the reinforced finger boundaries and finger crease patterns, thereby threshold is applied. We tracked the boundaries of the finger and extracted the Images of the index, middle, and ring finger, thereafter applied noise reduction operation. In the last step, we performed the verifications of a person by matching one dimensional profiles of finger crease patterns. This algorithm shows the possibility of an alternative biometrics identification system to the current ones. Lastly, the comparative evaluation on our system and the other algorithm is presented.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.112-115
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• 2020

Trump cards are used in variable games in households such as poker and blackjack. In many cases, it is able to be helpful to algorithmically identify the playing cards from camera views. In this paper, we provide an approach that detects and identifies the playing card using template matching scheme, and evaluate the results of the provided implementation. For ideal cases, the implemented system provides a 100% success rate for card identification correct. However, non-ideal case of perspective distortion is estimated with 70% success ratio. This work aims to evaluate the effectiveness of augmented reality user interface for an entertainment application like playing card games.