Dong-Min Woo

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In this paper, a new fragile watermarking algorithm for medical images is proposed. This algorithm makes it possible to resolve the security and forgery problem of the medical images. Instead of the discrete wavelet transform, an integer wavelet transform is used to utilize hash function. The watermark associated with the hash values is inserted into the(More)
The ability to efficiently and robustly recover accurate 3D terrain models from sets of stereoscopic images is important to many civilian and military applications. Our long-term goal is to develop an automatic, multi-image 3D reconstruction algorithm that can be applied to these domains. To develop an effective and practical terrain modeling system,(More)
This paper proposes a new blind watermarking scheme in which a watermark is embedded into the discrete wavelet transform (DWT) domain. The method uses the HVS model, and radial basis function neural networks (RBF). RBF will be implemented while embedding and extracting watermark. The human visual system (HVS) model is used to determine the watermark(More)
3D line segment can be regarded as one of the most useful features in constructing 3D model. In this context, this paper presents anew 3D line segment extraction method by using disparity map generated in the process of stereo matching. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by(More)
3D line segment can be regarded as one of the most useful features in constructing 3D model. In this context, this paper presents a new 3D line segment extraction method by using line fitting of elevation data on 2D line coordinates of ortho-image. In order to use elevation in line fitting, the elevation itself should be reliable. To measure the reliability(More)
This paper proposes a novel classification method for image retrieval using gradient-based fuzzy c-means with divergence measure (GBFCM(DM)). GBFCM(DM) is a neural network-based algorithm that utilizes the Divergence Measure to exploit the statistical nature of the image data and thereby improve the classification accuracy. Experiments and results on(More)
This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract the useful building location information from the generated disparity map to segment the interested objects and consequently reduce unnecessary line segments extracted in low level feature extraction step. Hypothesis selection is(More)
This paper presents a 3D camera calibration method based on a nonlinear modeling function of an artificial neural network. The neural network employed in this paper is primarily used as a nonlinear mapper between 2D image points and points of a certain space in 3D real world. The neural network model implicitly contains all the physical parameters, some of(More)