Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 24 for “"Scale-Invariant Feature Transform (SIFT)"”.
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Medical Image Registration Using Artificial Neural Network
<p>Image registration is the transformation of different sets of images into one coordinate system in order to align and overlay multiple images. Image registration is used in many fields such as medical imaging, remote sensing, and computer vision. It is very important in medical research, where …
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Ocular Biometrics: Human Recognition in Challenging Conditions
… a biometric. These methods include an optimized scale invariant feature transform (SIFT) and a fusion method utilizing SIFT and Gabor filter encoding.
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A Comparative Study of Feature Detection Methods for AUV Localization
… localizing the vehicle within the map. In SLAM, feature detection is used in landmark extraction and data association by examining each pixel and differentiating landmarks pixels from those of the background. Previous research on the performance of different feature detection methods have been …
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Agricultural Crop Monitoring with Computer Vision
… multispectral image registration, and the feature tracking of a stressed plant. The accuracy of several image segmentation methods are compared. Basic thresholding on pixel intensities and vegetation indices result in accuracies below 75% . Neural networks (NNs) and support vector machines …
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View synthesis for kinetic depth X-ray imaging
… thesis reports the development and analysis of feature based synthesis of transmission X-ray images. The synthetic imagery is formed through matching and morphing or warping line-scan format images produced by a novel multi-view X-ray machine. In this way video type sequences, which periodically …
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Super-resolution image reconstruction from low-resolution images
… for super-resolution based on a combination of Scale Invariant Feature Transform (SIFT), Belief Propagation (BP) and Random Sampling Consensus (RANSAC) is described to automatically register the low-resolution images. The results have shown effective for the removal of the mismatched features in …
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Organising and structuring a visual diary using visual interest point detectors
… similar backgrounds in images using their visual features. We present a number of approaches to setting detection based on the extraction of visual interest point detectors from the images. We also analyse the performance of two of the most popular descriptors - Scale Invariant Feature Transform …
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Investigating image processing algorithms for provision of information in rock art sites using mobile devices
… medium. Image processing algorithms such as Scale- Invariant Feature Transform (SIFT), Speeded-Up Robust Features (SURF) and Oriented Fast and Rotational Brief (ORB) have been incorporated in a mobile guide prototype and their performance has been evaluated. Performance evaluation has …
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Building Detection Using a Hybrid Methodology Applied to High Spatial Resolution Aerial Photographs
… in this hybrid methodology, including: Scale-Invariant Feature Transform (SIFT) feature extraction, K-Means (KMs) clustering, Bag-of-Visual-Words (BOVW) representation, Support Vector Machine (SVM), and Efficient Subwindow Search (ESS) techniques. This method was originally applied in …
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Object Detection and Recognition for Visually Impaired People
… content signage based on shape detection. Then, Scale-Invariant Feature Transform (SIFT) is applied to extract local features in the detected attended areas. Finally, signage is detected and recognized as the regions with the SIFT matching scores larger than a threshold. The proposed method can …
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Creating a virtual slide map from sputum smear images for region-of-interest localisation in automated microscopy
… was obtained at the expense of time using the scale invariant feature transform (SIFT), with a image registration error of 1 pixel2 (0.07 μm2). The object recognition algorithm is inherently robust to changes in slide orientation and placement, which are likely to occur in practice as it is …
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Vision task driven image super-resolution and image enhancement
… resulting in loss of performance. We develop a Scale-Invariant Feature Transform (SIFT) detection task-driven dark image enhancement method that learns the difference of Gaussian (DoG) pyramid from dark image input directly, with a cascade network that re-uses the network weights learned at …
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Remote monitoring and fault diagnosis of an industrial machine through sensor fusion
… Second, the sound and vibration signals are transformed into the frequency domain using fast Fourier transformation (FFT). A feature vector from the FFT frequency spectra is defined and extracted from the acquired information. Also, a feature based vision tracking approach—the Scale Invariant …
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Using regions of interest to track landmarks for RGBD simultaneous localisation and mapping
… time. The proposed algorithm extracts features from a region of interest (ROI) to track landmarks for RGBD SLAM. This strategy is compared to the traditional method of extracting features from an entire image. The ROI algorithm is implemented via a pre-processing algorithm, which is …
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Feature extraction for range image interpretation using local topology statistics
… based on the extraction and matching of local features from the images. In recent years, approaches to interpret two-dimensional (2D) images based on local feature extraction have advanced greatly, for example, systems such as Scale Invariant Feature Transform (SIFT) can detect and describe the …
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Parallelization of SIFT on Rigel
… at faster speeds to enable new usage models. SIFT is an algorithm for image detection and can be used for a variety of purposes. It collects key-point features that are invariant to changes in lighting, orientation and affine transforms. We ported the SIFT algorithm to the many-core …
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Novel color and local image descriptors for content-based image search
… to form the Color LBP Fusion (CLF) and Color Grayscale LBP Fusion (CGLF) descriptors that further improve image classification performance. Third, a new HaarHOG descriptor, which integrates the Haar wavelet transform and the Histograms of Oriented Gradients (HOG), is presented for extracting both …
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Investigation on advanced image search techniques
… for color image search. Specifically, a new oRGB-SIFT descriptor, which integrates the oRGB color space and the Scale-Invariant Feature Transform (SIFT), is proposed for image search and classification. The oRGB-SIFT descriptor is further integrated with other color SIFT features to produce the …
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Multimedia Content-Based Indexing and Recognition in Digital Libraries
… area of study for creating more advanced face/feature recognition algorithms. Before Eigenface was created, face recognition was done primarily by pinpointing key features on a face image, such as the eyes, nose, and mouth. However, this process proved to be slow and inefficient. With the …
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Unsupervised maritime target detection
… detection of maritime targets in grey scale video is a difficult problem in maritime video surveillance. Most approaches assume that the camera is static and employ pixel-wise background modelling techniques for foreground detection; other methods rely on colour or thermal information …
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