• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.18-26
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• 2008

The invariance relation existing in the non-negative matrix factorization (NMF) is used for constructing robust image hashes in this work. The image is first re-scaled to a fixed size. Low-pass filtering is performed on the luminance component of the re-sized image to produce a normalized matrix. Entries in the normalized matrix are pseudo-randomly re-arranged under the control of a secret key to generate a secondary image. Non-negative matrix factorization is then performed on the secondary image. As the relation between most pairs of adjacent entries in the NMF's coefficient matrix is basically invariant to ordinary image processing, a coarse quantization scheme is devised to compress the extracted features contained in the coefficient matrix. The obtained binary elements are used to form the image hash after being scrambled based on another key. Similarity between hashes is measured by the Hamming distance. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as Gaussian filtering, moderate noise contamination, JPEG compression, re-scaling, and watermark embedding. Hashes of different images have very low collision probability. Tampering to local image areas can be detected by comparing the Hamming distance with a predetermined threshold, indicating the usefulness of the technique in digital forensics.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.404-406
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• 1996

The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FFT, DWT(Discrete Wavelet Transform), and data compression are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 7-class power quality disturbances generated by the EMTP are also provided.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.18 no.4
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• pp.679-700
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• 1996

Inferior alveolar nerve dysfunction may be the result of trauma, disease, or iatrogenic injury. Inferior alveolar nerve injury is inherent risk in endodontic therapy, orthognathic surgery of the mandible, and extraction of mandibular teeth, particularly the third molars. The sensory disturbances of inferior alveolar nerve associated with such injury have been well documented clinical problem that is commonly evaluated by several clinical sensory test including Tinels sign, Von Frey test(static light touch detection), directional discrimination, two-point discrimination, pin pressure nociceptive discrimination, and thermal test. These methods used to detect and assess inferior alveolar nerve injury have been subjective in nature, relying on the cooperation of the patients. In addition, many of these techniques are sensitive to differences in the examiners experience and skill with the particular technique. Data obtained at different times or by different examiners are therefore difficult to compare. Prior experimental studies have used electro diagnostic methods(sensory evoked potential) to objectively evaluate inferior alveolar nerve after nerve injury. This study was designed with inferior alveolar nerve of rabbit. Several types of injury including mind, moderate, severe compression and perforation with 19 gauze, 21 gauze needle and 6mm, 10mm traction were applied for taking the sesory evoked ppterntial. Latency and amplitude of injury rabbit inferior alveolar nerve were investigated with sensory evoked potential using unpaired t-test. The results were as follows : 1. Intensity of threshold (T1) was $128{\pm}16{\mu}A$ : latency, $0.87{\pm}0.07$ microsecond : amplitude, $0.4{\pm}0.1{\mu}V$ : conduction velocity, 23.3 m/s in sensory evoked potential of uninjured rabbit inferior alveolar nerve. 2. Rabbit inferior alveolar nerve consists of type II and III sensory nerve fiber. 3. Latency was increased and amplitude was decreased in compression injury. The more injured, the more changed in latency and amplitude. 4. Findings in perforation injury was similar to compression injury. Waveform for sensory evoked potential improved by increasing postinjured time. 5. Increasing latency was prominent in traction injury rabbit inferior alveolar nerve. 6. In microscopic histopathological findings, significant degeneration and disorganization of the internal architecture were seen in nerve facicle of severe compression and 10mm traction group. From the above findings, electrophysiological assessment(sensory evoked potential) of rabbit injured inferior alveolar nerve is reliable technique in diagnosis and prognosis of nerve injury.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.258-261
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• 2014

The era of realistic broadcast with high fidelity has come after the wide-spread distribution of UHD display and the transmission of UHD experimental broadcast in CATV. However, UHD broadcast now has constraint because it requires much amount of bandwidth and data in broadcasting transmission and production system. Not only HEVC(High Efficiency Video Codec) which has more than two times higher compression rate but also cloud-based editing system would be the key to solve the problems above. Also, fast scene change detection of videos is needed to index and search UHD videos smoothly. In this paper, therefore, a method is proposed to index and search the scene change information of large volume UHD videos compressed with high-efficiency codec. Application usages of fast detection of scene change information in various UHD video environments are considered by using this algorithm.

• Journal of the Korean Institute of Gas
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• v.13 no.1
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• pp.45-51
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• 2009

A safety assessment was performed through the process analysis of hydrogen station. The purpose of this study provides basic information for the standard establishment about hydrogen stations. The processes of hydrogen stations were classified by four steps (process of manufacture, compression, storage, charge). FMEA (Failure Mode and Effect Analysis) method was applied to evaluate safety. Each risk element is following; S (severity), O (occurrence), D (detection). And the priority of order was decided by using RPN (Risk Priority Number) value multiplying three factors. Scenarios were generated based on FMEA results. And consequence analysis was practiced using PHAST program. In the result of C.A, jet fire and explosion were shown as accident types. In case of leakage of feed line in PSA process, concentration of CO gas is considered to prevent CO gas poisoning when the raw material that can product CO gas was used.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.292-297
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• 2013

In this paper, unusual waveform detection algorithm based on Refractory Period in arrhythmia ECG signal is proposed. Most of arrhythmia ECG signals consist of unusual waveforms with average 10% rate. Thus tremendous benefit can be obtained in terms of time and cost by providing unusual waveform samples reduced more than 90% to medical staffs who have to monitor and analyze for a long time. The proposed algorithm detects the R-peak using the features of R wave and variable refractory period. For the detected R-peak, unusual waveforms are found using means and standard deviation of electric potential and kurtosis of the R-peaks which are not included in unusual waveform. The proposed algorithm was applied to all records of the MIT-BIH arrhythmia database and showed more than average 90% of compression ratio.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4467-4486
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• 2018

Trying to deal with the problem of low robustness of Copy-Move Forgery Detection (CMFD) under various transformation and degradation attacks, a novel CMFD method is proposed in this paper. The main advantages of proposed work include: (1) Discrete Analytical Fourier-Mellin Transform (DAFMT) and Locality Sensitive Hashing (LSH) are combined to extract the block features and detect the potential copy-move pairs; (2) The Euclidian distance is incorporated in the pixel variance to filter out the false potential copy-move pairs in the post-verification step. In addition to extracting the effective features of an image block, the DAMFT has the properties of rotation and scale invariance. Unlike the traditional lexicographic sorting method, LSH is robust to the degradations of Gaussian noise and JEPG compression. Because most of the false copy-move pairs locate closely to each other in the spatial domain or are in the homogeneous regions, the Euclidian distance and pixel variance are employed in the post-verification step. After evaluating the proposed method by the precision-recall-$F_1$ model quantitatively based on the Image Manipulation Dataset (IMD) and Copy-Move Hard Dataset (CMHD), our method outperforms Emam et al.'s and Li et al.'s works in the recall and $F_1$ aspects.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.137-142
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• 2012

The temporal subtraction technique as one of computer aided diagnosis has been introduced in medical fields to enhance the interval changes such as formation of new lesions and changes in existing abnormalities on deference image. With the temporal subtraction technique radiologists can easily detect lung nodules on visual screening. Until now, two-dimensional temporal subtraction imaging technique has been introduced for the clinical test. We have developed new temporal subtraction method to remove the subtraction artifacts which is caused by mis-registration on temporal subtraction images of lungs on MDCT images. In this paper, we propose a new computer aided diagnosis scheme for automatic enhancing the lung nodules from the temporal subtraction of thoracic MDCT images. At first, the candidates regions included nodules are detected by the multiple threshold technique in terms of the pixel value on the temporal subtraction images. Then, a rule-base method and artificial neural networks is utilized to remove the false positives of nodule candidates which is obtained temporal subtraction images. We have applied our detection of lung nodules to 30 thoracic MDCT image sets including lung nodules. With the detection method, satisfactory experimental results are obtained. Some experimental results are shown with discussion.

• The KIPS Transactions:PartC
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• v.12C no.3 s.99
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• pp.379-386
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• 2005

Traditional watermarking technologies are symmetric method which embedding and detection keys are same. Although the symmetric watermarking method is easy to detect the watermark, has method has weakness against to malicious attacks to remove or modify the watermark information when the symmetric key is disclosure. Recently, the asymmetric watermarking method that has different keys to embed and detect is watched several researchers as a next generation watermarking technology. In this paper, we have expanded search space of secret key using the solution set of linear simultaneous equations. Secret key is generated by secure linear transformation method to prevent of guessing secret key from public key, and the correlation value between secret key and public key is high. At the results, the multi bits information can be embedded and high correlation value was detected after JPEG compression.