• International Journal of Computer Science & Network Security
• /
• v.21 no.12spc
• /
• pp.451-458
• /
• 2021

Providing a secure and effective way to protect confidential and private data is an urgent process, and accordingly, we will present in this research paper a new method, which is called multiple rounds variable block method (MRVB) which depends on the use of a colored image that is kept secret to generate needed work and round keys. This method can be used to encrypt-decrypt data using various lengths private key and data blocks with various sizes. The number of rounds also will be variable starting from one round. MRVB will be implemented and compared with the encryption-decryption standards DES and AES to show the improvements provided by the proposed method in increasing the security level and in increasing the throughput of the process of data cryptography. The generated private key contents will depend on the used image_key and on the selected number of rounds and the selected number of bytes in each block of data.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.5
• /
• pp.155-162
• /
• 2008

The security of digital image has become increasingly important with the development of the computing performance and internet. Therefore, the encryption algorithms exploiting chaos signal have recently attracted considerable attentions as a new method of image-encryption techniques. In this Paper, it is demonstrated that two different chaotic systems are synchronized by the methods of noise-induced synchronization. Based on this synchronization method, an image-encryption system is implemented and an image of Seok-Ga-Tap is encrypted as a verification of the performance of our system. The method suggested in this paper in which the noise is used as the key of decryption is superior to the existing methods in the aspect of the degree of encryption. In this paper, we Propose that the method is a new effective encryption algorithm as well as an easily applicable one.

• Journal of the Semiconductor & Display Technology
• /
• v.22 no.4
• /
• pp.108-112
• /
• 2023

Precision manufacturing technology is rapidly developing due to the extreme miniaturization of semiconductor processes to comply with Moore's Law. Accurate and precise alignment, which is one of the key elements of the semiconductor pre-process and post-process, is very important in the semiconductor process. The center detection of wafer align marks plays a key role in improving yield by reducing defects and research on accurate detection methods for this is necessary. Methods for accurate alignment using traditional image sensors can cause problems due to changes in image brightness and noise. To solve this problem, engineers must go directly into the line and perform maintenance work. This paper emphasizes that the development of AI technology can provide innovative solutions in the semiconductor process as high-resolution image and image processing technology also develops. This study proposes a new wafer center detection method through variable thresholding. And this study introduces a method for detecting the center that is less sensitive to the brightness of LEDs by utilizing a high-performance object detection model such as YOLOv8 without relying on existing algorithms. Through this, we aim to enable precise wafer focus detection using artificial intelligence.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.3
• /
• pp.10-19
• /
• 2009

In this paper, an efficient optical watermark method using multiple phase wrapping and real-valued decoding key is proposed. In the embedding process, two zero-padded original images placed in two quadrants on input plane are multiplied with two statistically independent random phase patterns and are Fourier transformed, respectively. Two encoded images are obtained by taking the real-valued data from these Fourier transformed images. And then two phase-encoded patterns, used as a hidden image and a decoding key, are generated by the use of multiple phase wrapping from each of the encoded images. A transmitted image is made from the linear superposition of the weighted hidden images and a cover image. In reconstruction process, the mirror reconstructed images can be obtained at all quadrants by the inverse-Fourier transform of the product of the transmitted image and the decoding key. Computer simulation and optical experiment are demonstrated in order to confirm the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.2
• /
• pp.10-23
• /
• 2009

The fundamental matrix and key frame selection are one of the most important techniques to recover full 3D reconstruction of objects from turntable sequences. This paper proposes a new algorithm that estimates a robust fundamental matrix for camera calibration from uncalibrated images taken under turn-table motion. Single axis turntable motion can be described in terms of its fixed entities. This provides new algorithms for computing the fundamental matrix. From the projective properties of the conics and fundamental matrix the Euclidean 3D coordinates of a point are obtained from geometric locus of the image points trajectories. Experimental results on real and virtual image sequences demonstrate good object reconstructions.

• Proceedings of the IEEK Conference
• /
• 2000.06d
• /
• pp.222-225
• /
• 2000

Human frequently communicate non-linguistic information with gesture. So, we must develop efficient and fast gesture recognition algorithms for more natural human-computer interaction. However, it is difficult to recognize gesture automatically because human's body is three dimensional object with very complex structure. In this paper, we suggest a method which is able to detect key frames and frame changes, and to classify image sequence into some gesture groups. Gesture is classifiable according to moving part of body. First, we detect some frames that motion areas are changed abruptly and save those frames as key frames, and then use the frames to classify sequences. We symbolize each image of classified sequence using Principal Component Analysis(PCA) and clustering algorithm since it is better to use fewer components for representation of gestures. Symbols are used as the input symbols for the Hidden Markov Model(HMM) and recognized as a gesture with probability calculation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.5
• /
• pp.2171-2185
• /
• 2020

In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.1
• /
• pp.102-107
• /
• 2004

In this paper, we proposed a content-based image retrieval system using the multi-Index key. The multi-index ky combines the color distribution considering the spatial characteristic and the shape features of an image using the edge detection. Consequently, the evaluation shows that the performance of the proposed technique is better than other techniques.

• Proceedings of the KIEE Conference
• /
• 2002.11c
• /
• pp.569-572
• /
• 2002

In this study, a real-time image composition system was implemented using chroma key algorithm. To write a high Quality chroma key function based on processing of foreground and/or background frames before combining them into an output image, Adaptive 3-dimensional surface equation model was proposed. When the bright of room is changed or shadow of object is on the blue screen, proposed algorithm would still produce good result.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.7
• /
• pp.2919-2937
• /
• 2020

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.