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For geoscientific applications, automatic shape-based feature detection offers a fast and non-subjective means of identifying geological structures within data. Most previously published examples of circular feature detection for geoscientific applications aimed to identify impact craters from optical or topographic data. Various techniques used include the Hough transform, template matching, and...
Visualization of the patient-specific fractured bone in three dimensions (3D) plays an important role in image guided orthopedic surgery. Existing research often focuses on intra-operative registration of the patientspsila anatomy with pre-operatively obtained 3D volumetric data (e.g. CT scans) utilizing fiduciary markers. This expensive and invasive approach is not routinely available for diagnostics,...
Markerless human motion capture has received much attention in computer vision and computer graphics communities. A hierarchical skeleton template is frequently used to model the human body in literature, because it simplifies markerless human motion capture as a problem of estimating the human body shape and joint angle parameters. The proposed work establishes a skeleton based markerless human motion...
This paper adopts skeletonization approach to represent Chinese character and uses the resulting written strokes for optimized matching. We use shortest path method that represented by end node pair and junction node pair in the character for matching. This strategy is improved from the original shortest skeleton path matching by introducing the junction node as an extra feature in order to be able...
Many fatal accidents have happened due to drivers failing to stop at stop signs. A stop sign recognition system could be used to reduce the risk of accidents by warning the driver when a vehicle approaches a stop sign at an unexpected speed. In this paper, we describe the implementation of a real-time vision-based stop sign recognition system on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA)...
Recently, semantic image retrieval has attracted large amount of interest due to the rapid growth of digital image storage. However, existing approaches have severe limitations. In this paper, a new approach to digital image retrieval using intermediate semantic features and multistep search has been proposed. Instead of looking for human level semantics which is too challenging at this stage, the...
Two variants of the SIFT algorithm are presented which operate on calibrated central projection wide-angle images characterised as having extreme radial distortion. Both define the scale-space kernel, termed the spherical Gaussian, as the solution of the heat diffusion equation on the unit sphere. Scale-space images are obtained as the convolution of the image mapped to the sphere with the spherical...
In this paper, it is intended to accurately separate pixels related to two spectrally similar classes of building and road in Shiraz urban area. To achieve this goal, Support Vector Machine (SVM) classification algorithm has been applied to a Landsat ETM+ image of Shiraz City. In order to assess the accuracy of the results, Maximum Likelihood Classification (MLC) as an approved and conventional algorithm...
This study proposes a classification-based facial expression recognition method using a bank of multilayer perceptron neural networks. Six different facial expressions were considered. Firstly, logarithmic Gabor filters were applied to extract the features. Optimal subsets of features were then selected for each expression, down-sampled and further reduced in size via principal component analysis...
This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, and Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For preprocessing and feature extraction steps, we apply a combination of wavelet transform and PCA. During...
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