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 15 of 15 for “"Over-segmentation"”.
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Computer vision system for identifying road signs using triangulation and bundle adjustment
… algorithm are applied to the images to achieve over-segmentation. The novel second phase ensures over-segmentation without excessive computation. Extremely large and very small segments are rejected. The remaining segments are then classified based on color. Finally, the frame to frame …
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Scalable algorithms for semi-automatic segmentation of electron microscopy images of the brain tissue
… of the neurons require fast and accurate image segmentation algorithms. Due to the sheer size of the problem, traditional approaches might be computationally infeasible. I focus on an segmentation pipeline that breaks up the segmentation problem into multiple stages, each of which can be …
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Image and Color Stylization through Region-based Abstraction
… We propose an abstraction method based on an over-segmentation through overlapping region growth. The main idea of this method is to create stylized images by complex primitives. Unlike traditional over-segmentation methods, this method emphasizes the irregularity of region shape even in …
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Multi-resolution region-preserving segmentation for color images of natural scene
Image segmentation is one of the primary steps in image analysis for image labeling and retrieval. Recent Segmentation methods have shown a strong interest in graph based algorithm, and they have been quite successful in identifying significant regions and their boundaries. The cost functions used …
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Contribution au classement des fruits par analyse d'images numériques. Application au tri en ligne des pommes Golden delicious et Jonagold.
… into account local information, enhanced the segmentation precision. The calyx and stem ends, which appear as defects on the image, were detected by a pattern correlation technique. The segmented areas (poles, defects and over-segmentation zones) were characterised with shape, colour and …
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Supervoxel Based Object Detection and Seafloor Segmentation Using Novel 3d Side-Scan Sonar
Object detection and seafloor segmentation for conventional 2D side-scan sonar imagery is a well-investigated problem. However, due to recent advances in sensing technology, the side-scan sonar now produces a true 3D point cloud representation of the seafloor embedded with echo intensity. This …
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Learning to Segment Images Into Material and Object Classes
… With regards to opaque objects an initial segmentation can be constructed using local features within regions produced from an over segmentation of the image. Our interest here is in improving these local segmentations by incorporating global information. Using global features (i.e. …
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Parallel and scalable neural image segmentation for connectome graph extraction
Segmentation of images, the process of grouping together pixels of the same object, is one of the major challenges in connectome extraction. Since connectomics data consist of large quantity of digital information generated by the electron microscope, there is a necessity for a highly scalable …
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Superpixel Segmentation of Outdoor Webcams to Infer Scene Structure
… orientation; and thus the 3-D structure of the overall scene. Previous works have studied the time-series brightness of individual pixels. However, there are limitations with this approach. Pixels are often quite noisy, and can require a lot of memory. This thesis explores the use of superpixels …
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Segmentation and Fracture Detection in X-ray images for Traumatic Pelvic Injury
… system therefore incorporates a hierarchical segmentation algorithm which is able to automatically extract multiple structures in a single pass, using a combination of anatomical knowledge and computational techniques such as directed Hough Transform. This algorithm also applies a novel …
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Minimal Labels, Maximum Gain. Image Classification with Graph-Based Semi-Supervised Learning
… learning models we need large datasets to reduce over-fitting. Acting as a potential solution, the paradigm of semi-supervised learning extracts information from both labelled and unlabelled data and reduces the number of labels needed for training. This thesis deals with the development of novel …
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The missing link in as-built 3D modeling: geometrical labeling of segmented point clouds for fitting geometrical surface
… bottlenecks of the process: the first can spread over a few days, and the latter can span over multiple weeks or even months. In consequence, the applicability of as-built modeling has been traditionally restricted to high latency analysis, where the model need not be updated frequently. In fast …
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Semantically-rich as-built 3D modeling of the built environment from point cloud data
… bottlenecks of the process: the first can spread over a few days, and the latter can span over multiple weeks or even months. Hence, the applicability of as-built modeling has been traditionally restricted to high latency analysis, where the model need not be updated frequently. In fast changing …
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Application of Machine Learning and Deep Learning Methods in Geological Carbon Sequestration Across Multiple Spatial Scales
… with advanced numerical simulations. Image segmentation is a crucial step of the DRP framework, affecting the accuracy of the following analyses and simulations. We proposed a DL-based workflow for boundary and small target segmentation in digital rock images, which aims to overcome the main …
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THE DEVELOPMENT AND EVALUATION OF TECHNIQUES FOR USE IN MAMMOGRAPHIC SCREENING COMPUTER AIDED DETECTION SYSTEMS
… domain knowledge along with a simple threshold segmentation algorithm. Once this image area of interest is specified, contained objects of interest are identified using Iterative Disjoint Region Detection (IDRD). This specialized procedure utilizes iterative threshold segmentation to produce a …