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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)
A new code excited linear predictive (CELP) vocoder based on Adaptive Multi Rate (AMR) 7.4 kbit/s mode is proposed in this paper. The proposed vocoder achieves a better compression rate in an environment of Speaker Dependent Coding System (SDSC) and is efficiently used for systems, such as OGM (Outgoing message) and TTS (Text To Speech), that stores the(More)
An unsupervised competitive neural network for efficient classification of image textures is proposed. The proposed neural network architecture, called centroid neural network with Chi square distance measure (CNN-&#x03C7;<sup>2</sup>), employs the Chi square measure as its distance measure and utilizes the local binary pattern (LBP) as an effective feature(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)