Seung-Hoon Chae

A Study on the Korean Banknote Recognition Using RGB and UV Information

Since the utilization of finance self-service is getting increment, bank and financial institutions has provided various services using automatic banking systems. For better efficiency of utilization of automatic banking system, banknote recognition, performing banknote classification and counterfeit detection, is getting more important. This paper used color and UV information of bankonte for banknote recognition. We have improved the accuracy of banknote classification by classify the candidate of the kind of banknote and then applying size information of the banknote. Counterfeit detection is performed to comparing UV information of reference and input image after banknote classification. Our experimental results show that the performance of banknote classification and counterfeit detection are 99.1% and 98.3%.

Dual Watermarking Method for Integrity of Medical Images

As medical images are created, displayed, transmitted or stored in a digital form, there has been a growing interest in protecting the medical images against external/internal attackers. In this paper, we propose a dual watermarking method(DWM) to protect medical images in transmission/storage. As the proposed DWM provides both robustness and fragileness with the embedded watermarks, it can guarantee the integrity of the medical image transmitted and/or stored. In DWM, watermarks are carefully embedded avoiding the areas of region of interest(ROI) and the edge of the contents to protect the integrity of the medical image. Based on experimental results, we confirm that our DWM can detect the robust watermark accurately and detect the intentional/unintentional leakage of the transmitted or stored medical image.

Automatic lung segmentation for large-scale medical image management

Digital medical images assist specialists in improving their diagnostic efficiency and in treating diseases. For example, the chest Computed Tomography (CT) images help in diagnosing the lung disease. The chest CT scan generates multiple images of a patient’s lung. The size of the medical imaging data has increased with the usage of medical images. In a picture archiving and communication system, large-scale medical images must be transmitted to specialists through either wired or wireless communications and retained in the archive. Hence, medical images have to be compressed, and there should be no damage to the Region of Interest (RoI) during compression. In order to protect the RoI, image segmentation is needed to detect RoI in medical images. Among the various image segmentation methods available, the method using Level-set is robust to irregular noises. However, the problems faced in using this method include manual input of the initial contour and slow performance speed. Inputting an initial contour to the Level-set that correctly fits the object’s form helps in reducing the number of repetitions. This in turn helps in improving the segmentation performance speed. However, it is difficult for a user to input an appropriate initial contour. Therefore, this paper aims at providing a method to auto-configure the initial contour in the Level-set method. Multi-resolution analysis helps in reducing the pace of the auto-configuration process of the initial contour. In addition, the volume data of a CT image is used to prevent data loss that occurs during the MRA transformation process. Studies have confirmed that the proposed method facilitates drastic improve.

Parallel Processing of the Fuzzy Fingerprint Vault based on Geometric Hashing

User authentication using fingerprint information provides convenience as well as strong security. However, serious problems may occur if fingerprint information stored for user authentication is used illegally by a different person since it cannot be changed freely as a password due to a limited number of fingers. Recently, research in fuzzy fingerprint vault system has been carried out actively to safely protect fingerprint information in a fingerprint authentication system. In addition, research to solve the fingerprint alignment problem by applying a geometric hashing technique has also been carried out. In this paper, we propose the hardware architecture for a geometric hashing based fuzzy fingerprint vault system that consists of the software module and hardware module. The hardware module performs the matching for the transformed minutiae in the enrollment hash table and verification hash table. On the other hand, the software module is responsible for hardware feature extraction. We also propose the hardware architecture which parallel processing technique is applied for high speed processing. Based on the experimental results, we confirmed that execution time for the proposed hardware architecture was 0.24 second when number of real minutiae was 36 and number of chaff minutiae was 200, whereas that of the software solution was 1.13 second. For the same condition, execution time of the hardware architecture which parallel processing technique was applied was 0.01 second. Note that the proposed hardware architecture can achieve a speed-up of close to 100 times compared to a software based solution.

JPEG 2000 and Digital Watermarking Technique Using in Medical Image

The Picture Archiving and Communication System(PACS) was introduced for computerization of the medical system and telediagnosis between the hospital. It is becoming possible to create, store, and transmit medical images via PACS. There has been a growing interest in protecting medical images with an enormous amount of information. To improve transmission speed among the hospitals, the medical image should be compression JPEG 2000 by high compression ratio. This paper proposes an algorithm that utilizes both JPEG 2000 and robust watermarking for protection and compression of the medical image. With the proposed algorithm, it takes considerably less time to do JPEG 2000 and watermarking than when they are done separately. Based on the experiment results, it takes 0.72 second for the proposed algorithm and 1.11 second when they are done separately. We confirmed that the proposed algorithm was faster than when they are done separately.

Ridge-based fingerprint verification for enhanced security

Fingerprint verification systems are very convenient and secure. However, existing systems can cause errors according to size and quality of fingerprint images that are read only with a use of minutiae. This paper enhanced security performance by decreasing False Match Rate(FMR) through a fingerprint verification system for which both minutiae and ridge information are used. As a result, we found that ZeroFMR decreased from 29% to 9.9%, which indicates enhanced security performance.

Intelligent video surveillance system using two-factor human information

Recently, with the increase of terror and crime the utilization of security surveillance systems including CCTV increases. However, the issues of privacy invasion occurred by exposing the data recorded through video surveillance system have been raised. In this paper, the intelligent video surveillance system which can prevent the invasion of privacy and complement the monitoring function which will be declined by privacy protection is proposed. The proposed system checks the identification using the smart card and camera at the entrance and extracts the height and color information of object. Inside of the building where only a camera is installed without smart card terminal installed checks the identification using height and color information of object. With the implemented identification function the proposed system sorts the object receiving the privacy protection, implements the monitoring function and provides monitoring and protection function at the same time.

Simplified false-positive reduction in computer-aided detection scheme of clustered microcalcifications in digital breast tomosynthesis

A computer-aided detection (CADe) system for clustered microcalcifications (MCs) in reconstructed digital breast tomosynthesis (DBT) volumes was suggested. The system consisted of prescreening, MC detecting, clustering, and falsepositive reduction steps. In the prescreening stage, the MC-like objects were enhanced by a multiscale-based 3D calcification response function. A connected component segmentation method was used to detect cluster seed objects, which were considered as potential clustering centers of MCs. Starting with each cluster seed object as the initial cluster center, a cluster candidate was formed by including nearby MC candidates within a 3D neighborhood of the cluster seed object satisfying the clustering criteria during the clustering step. The size and number of the clustered MCs in a cluster seed candidate were used to reduce the number of FPs. A bounding cube for each MCC was generated for each accepted seed candidates. Then, the overlapping cubes were combined and examined according to the FP reduction criteria. After FP reduction step, we obtained the average number of FPs of 2.47 per DBT volume with sensitivity of 83.3%. Our study indicates the simplified false-positive reduction approach applied to the detection of clustered MCs in DBT is promising as an efficient CADe system.

Four-Joint Based Motion Capture for Spinal Disease Prevention System

ABSTRACT Bad posture triggers spinal diseases by forming a twisted or crooked body. Therefore, it is vital for modern people mostly living a sedentary lifestyle to have correct posture. Thanks to rising demand in the health care sector and advancement of information technology these days, the development of a self-coaching system is underway using motion capture technology. With the self-coaching system applied to rehabilitation exercises or the sports field, subjects using the system can practice and learn rehabilitation exercises or sports motions on their own without any help. It is necessary to acquire and analyze motion data both from experts for coaching purposes and users who are being coached in order to develop the self-coaching system. The existing motion capture system has a drawback in that it is difficult to make smooth and natural motions because it uses heavy machines or a wired system. In this paper, we proposed a reasonably priced motion capture system requiring less preparation time and measurement space by using small-sized and lightweight microelectromechanical systems-based wireless inertial sensors to address the problems with the existing motion capture system. The analysis results show that the motion data of four joints acquired through the embodied system can be applied to the self-coaching system, and users can employ the system for spinal disease diagnosis themselves.

Security Enhancement for Smartphone Using Biometrics in Cyber-Physical Systems

With the expansion of the Cyber-Physical System (CPS) concept, smartphones have come to constitute a competitive platform that connects humans and the surrounding physical world. Along with the communication functions and mobility of cellular phones, smartphones have various sensors in addition to greatly enhanced performances and storage space compared with existing cellular phones. However the “unlock” process of smartphones and the need for user passwords when accessing SNSs prove to be great weaknesses in smartphone security. Therefore, smartphone security should be enhanced through biometrics, which can make up for the shortcomings of passwords. The present study proposes minutiae-ridge based fingerprint verification for enhancing the security of fingerprint verification, a biometrics, to improve smartphone security. To evaluate the proposed minutiae-ridge based fingerprint verification performance in smartphones, its performance was compared with existing fingerprint verification methods in terms of Equal Error Rate (EER), False Non-Match Rate (FNMR), and required number of cycles. The results show that although the required number of cycles increased by 1.5% with the proposed method, EER and FNMR improved by 53% and 92%, respectively.