• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.11A
• /
• pp.870-881
• /
• 2009

The rapid development of healthcare information management for 3D medical digital library, 3D PACS and 3D medical diagnosis has addressed security issues with medical IT technology. This paper presents multiple 3D medical image data for protection, authentication, indexing and diagnosis information hiding applied to healthcare information management. The proposed scheme based on POCS watermarking embeds the robust watermark for doctor's digital signature and information retrieval indexing key to the distribution of vertex curvedness and embeds the fragile watermark for diagnosis information and authentication reference message to the distance difference of vertex. The multiple embedding process designs three convex sets for robustness, fragileness and invisibility and projects 3D medical image data onto three convex sets alternatively and iteratively. Experimental results confirmed that the proposed scheme has the robustness and fragileness to various 3D geometric and mesh modifiers at once.

• Journal of Korea Multimedia Society
• /
• v.6 no.2
• /
• pp.247-258
• /
• 2003

Principal component analysis (PCA) based algorithms form the basis of numerous algorithms and studies in the face recognition literature. PCA is a statistical technique and its incorporation into a face recognition system requires numerous design decisions. We explicitly take the design decisions by in-troducing a generic modular PCA-algorithm since some of these decision ate not documented in the literature We experiment with different implementations of each module, and evaluate the different im-plementations using the September 1996 FERET evaluation protocol (the do facto standard method for evaluating face recognition algorithms). We experiment with (1) changing the illumination normalization procedure; (2) studying effects on algorithm performance of compressing images using JPEG and wavelet compression algorithms; (3) varying the number of eigenvectors in the representation; and (4) changing the similarity measure in classification process. We perform two experiments. In the first experiment, we report performance results on the standard September 1996 FERET large gallery image sets. The result shows that empirical analysis of preprocessing, feature extraction, and matching performance is extremely important in order to produce optimized performance. In the second experiment, we examine variations in algorithm performance based on 100 randomly generated image sets (galleries) of the same size. The result shows that a reasonable threshold for measuring significant difference in performance for the classifiers is 0.10.

• Journal of Internet Computing and Services
• /
• v.24 no.4
• /
• pp.85-92
• /
• 2023

Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.10
• /
• pp.1305-1313
• /
• 1995

In this paper, we propose a robust estimation of camera parameters from image sequence for high quality video composition. We first establish correspondence of feature points between consecutive image fields. After the establishment, we formulate a nonlinear least-square data fitting problem. When the image sequence contains moving objects, and/or when the correspondence establishment is not successful for some feature points, we get bad observations, outliers. They should be properly eliminated for a good estimation. Thus, we propose an iterative algorithm for rejecting the outliers and fitting the camera parameters alternatively. We show the validity of the proposed method using computer generated data sets and real image sequeces.

• Journal of the Korea Society of Computer and Information
• /
• v.3 no.2
• /
• pp.113-117
• /
• 1998

The image recognition, with various technics, recently presented an effective recognition scheme both for image and character. The analyzing process, however, is highly complicated so that this does not utilized fully. This paper examines the validity of the image recognition through morphology, which is simple and a theory of sets. The morphology applies erosion and dilation, opening and closing, and structuring element.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.25-27
• /
• 2009

This paper presents the stereoscopic conversion of flame images. The stereoscopic conversion is a technology that generates left and right images from a monoscopic image. Even though many conversion methods have been introduced and commercialized so far, the processing of flame images is relatively few. Such conventional methods are effectively used either real-time or off-line. However, the application of such schemes to special-effect images such as flame is hard to be applied. The proposed method is designed to convert a flame image into a stereoscopic image. Depth map of flame regions are produced based on the analysis of color models of flames. Experimental results tested on diverse flame image sets validates the effectiveness of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.8 no.2 s.21
• /
• pp.14-21
• /
• 2005

This paper describes the system for detecting the tank crew's(loader's) hand, arm, head and the upper half of the body in a danger area between the turret ceiling and the upper breech mechanism by computer vision-based method. This system informs danger of pressed to death to gunner and commander for the safety of operating mission. The camera mounted ort the top portion of the turret ceiling. The system sets search moving object from this image and detects by using change of image, laplacian operator and clustering algorithm in this area. It alarms the tank crews when it's judged that dangerous situation for operating mission. The result In this experiment shows that the detection rate maintains in $81{\sim}98$ percents.

• Korean Journal of Remote Sensing
• /
• v.22 no.5
• /
• pp.351-356
• /
• 2006

Based on current practical needs for geo-spatial information on mobile platform, the main theme of this study is a design and implementation of dynamic 3D terrain rendering system using spaceborne imagery, as a kind of texture image for photo-realistic 3D scene generation on mobile environment. Image processing and 3D graphic techniques and algorithms, such as TIN-based vertex generation with regular spacing elevation data for generating 3D terrain surface, image tiling and image-vertex texturing in order to resolve limited resource of mobile devices, were applied and implemented by using graphic pipeline of OpenGL|ES (Embedded System) API. Through this implementation and its tested results with actual data sets of DEM and satellite imagery, we demonstrated the realizable possibility and adaptation of complex typed and large sized 3D geo-spatial information in mobile devices. This prototype system can be used to mobile 3D applications with DEM and satellite imagery in near future.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.11a
• /
• pp.73-76
• /
• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.04a
• /
• pp.405-408
• /
• 2010

This paper presents a new feature extraction technique, correlation coefficient and Manhattan distance (MD) based method for recognition of rotated object in an image. This paper also represented a new concept of intensity invariant. We extracted global features of an image and converts a large size image into a one-dimensional vector called circular feature vector's (CFVs). An especial advantage of the proposed technique is that the extracted features are same even if original image is rotated with rotation angles 1 to 360 or rotated. The proposed technique is based on fuzzy sets and finally we have recognized the object by using histogram matching, correlation coefficient and manhattan distance of the objects. The proposed approach is very easy in implementation and it has implemented in Matlab7 on Windows XP. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated images.