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A system employing entropy reduction on layout data to manage and track physical intellectual property (IP) is presented. Using a combination of symbolic encoding, canonical reduction, lossless compression and cryptographic hash functions, this system provides an efficient, scalable, robust and extensible method for tracking geometrical layout from design through manufacturing and into production...
Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we present a novel view-dependent algorithm that can minimize occlusion and reveal important flow features for three dimensional flow fields. To analyze regions of higher importance, we utilize Shannon's entropy as a measure of vector complexity...
It is well known that the noise in magnetic resonance (MR) magnitude images obeys a Rician distribution. Denoising of MR images is of importance for clinical diagnosis and computerized analysis, such as tissue classification, segmentation, and registration. We propose a post-acquisition denoising algorithm in an attempt to automatically remove the random fluctuations and bias introduced by Rician...
Face recognition has a wide range of possible applications in surveillance, access control, human computer interfaces and in electronic marketing and advertising for selected customers. Several models based on Gabor feature extraction have been proposed for face recognition with very good results on internationally available face databases. In this paper, we propose a methodological improvement to...
In this paper, we discuss the extraction of relations between lecturer and students in lectures by using multi-layered neural networks. Here, the relations among a few features concerning on the behaviors of the lecturer and students can be represented by multi-layered neural networks with the time-delay. Furthermore, we introduce a structural learning algorithm with forgetting for neural networks...
Investigating multi-feature information-theoretic image registration, we introduce consistent and asymptotically unbiased kth-nearest neighbor (kNN) estimators of mutual information (MI), normalized MI and exclusive information applicable to high-dimensional random variables, and derive under closed-form their gradient flows over finite- and infinite-dimensional transform spaces. Using these results,...
The registration of breast DCE-MR images can help correct possible motions during image acquisition, and is also important for diagnosis of breast cancer, i.e., discrimination between benign and malignant tumors. However, deformable registration of DCE-MR images is challenging due to drastic image contrast change over time (especially between pre- and post-contrast images). To improve the registration,...
Online measurement of wheel set wear parameters is important for train safety. The acquisition and processing of wheel set profile image is a key problem in online measuring based on machine vision. Appropriate threshold segmentation is needed to extract clear wheel set profile curve from varying background. Otsu algorithm is the traditional optimal threshold method, which is popular and efficient,...
In this paper we propose a novel approach for the robust estimation of room structure using Manhattan world assumption i.e. the frequently observed dominance of three mutually orthogonal vanishing directions in man-made environments. First, separate histograms are generated for every major axis, i.e. X, Y and Z, on stereo data with an arbitrary roll, pitch and yaw rotation. These histograms are maintained...
Topology free structure of scanning electron microscopy images of heat treated, metallized compound semiconductor surfaces are studied using structural entropy based analysis. The scale dependence and the possible superstructures are determined by wavelet transforming the images before the localization type detection. The studied images are taken in-situ during a thermalization experiment, using GaAs...
The problem of compositing a high dynamic range (HDR) image for display on a standard low dynamic range device involves matte-based fusion of multiple images captured with different camera exposures, followed by a suitable tone mapping of the fused HDR image. The fused image should represent the entire scene in a clear, well-exposed manner by bringing the under- and over-exposed regions from the input...
A visual cue is introduced that exploits the visual appearance of a single image to estimate the proximity to an obstacle. In particular, the appearance variation cue captures the variation in texture and / or color in the image, and is based on the assumption that there is less such variation when the camera is close to an obstacle. Random sampling is applied in order to evaluate the appearance variation...
The hybrid coding method combining the predictive coding with the orthogonal transformation and the quantization is mainly used recently. This paper proposes a new hybrid parallel Intra Coding based on interpolative prediction which uses correlations between neighboring pixels, including non-causal pixels. In order to get high prediction performance, the optimal quantizing scheme, which is used to...
Edge detection is important step in image processing. In spite of two decade of research the need for general purpose edge detector is still felt. Threshold decision is the key uncertainty in the edge detection algorithms. Soft computing approach represents a good mathematical framework to deal with uncertainty of information. In this work, we used fuzzy logic for automatic thresholding and generated...
In modern multimedia applications there is a constant increase of the need for more computational power, flexibility and memory availability. The answer for this demand comes from MPSoC platforms implemented on powerful FPGA devices, where high performance and a vast system architecture design flexibility is offered. Whilst many groups are targeting their research on developing automated tools for...
In this paper, we propose a multi-scale matching approach to address the data association problem in vision-based simultaneous localization and mapping (SLAM). Data association in vision-based SLAM can be simply represented as a feature correspondence problem related to two features observed in different positions under different imaging conditions. We apply an improved Harris detector to automatically...
This paper presents a novel architecture for a classification system based on the visual saliency of images. The work is motivated by the difficulty of reviewing large numbers of images as a human operator in the context of Autonomous Underwater Vehicle (AUV) surveys. We formulate a feature space in which an algorithm operates over color and texture to determine saliency and illustrate how this can...
A method of viscose filament fracture surface image segmentation based on SOFM network fusion is proposed. Firstly, the binarization method based on two-way weighting sequential smooth is used to segment the two images which are obtained in different light intensity. Secondly, fuse the two binary images based on SOFM fusion. After that, the final segmentation image is obtained. Using this method can...
Matching region selection is one of the bases of underwater terrain-aided navigation technology. Boundary division of topographic statistical map, which provides convenience to matching region selection and route planning, can be accomplished quickly when using image edge detection on it. This article firstly introduced the characteristics of edge detection operators; the grayscale image was transformed...
As the coverage area of the sub-block is too large, the texture feature clustering based on sub-block often produces the mosaic phenomenon of inaccurate boundary. In this paper, the texture clustering algorithm based on pixel extracts the texture feature vector of its central pixel point from sub-block. The image texture feature is standardized, then the normalized feature vector is clustered and...
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