Inhaltsangabe
Seminar paper from the year 2020 in the subject Engineering - Computer Engineering, grade: 1,0, University of Applied Sciences Ulm, language: English, abstract: Unlock the secrets of sight in machines with this deep dive into computer vision, a field where algorithms learn to 'see' the world as we do. Journey from the theoretical underpinnings of image analysis to the practical application of feature detection and matching, unraveling the complexities of how computers identify and interpret visual information. This exploration meticulously dissects core methodologies, bridging the gap between abstract mathematical concepts and hands-on implementation using Python and the powerful OpenCV library. Discover the inner workings of feature detection algorithms, including the widely used SIFT algorithm, and grasp the nuances of adaptive non-maximal suppression (ANMS) in pinpointing key image features. Master the art of feature matching, employing strategic techniques to establish correspondences between images, and delve into the crucial aspects of feature repeatability and invariance, ensuring robust performance across varying image conditions. Ascend to the realm of edge detection, where algorithms like Laplacian of Gaussian and the Canny edge detector carve out the boundaries that define objects. This comprehensive guide not only elucidates the theoretical foundations but also provides a pathway to practical mastery, equipping you with the skills to develop your own computer vision applications. Whether you're a student, a researcher, or a seasoned developer, this resource will empower you to navigate the intricate landscape of image processing, transforming raw pixels into meaningful insights and unlocking the potential of visual intelligence. Explore the intricacies of image analysis, delve into the world of feature tracking, and uncover the power of computer vision to revolutionize industries ranging from robotics to medical imaging. This is your gateway to understanding how machines perceive and interact with the visual world, paving the way for a future where technology truly sees eye-to-eye with humanity. Prepare to embark on a transformative journey that will reshape your understanding of visual information and unlock a world of possibilities in the realm of artificial intelligence and machine perception, all through the lens of computer vision, feature detection, and intelligent image analysis.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Suchergebnisse für Feature Detection and Matching. Computer Vision
Foto des Verkäufers
Feature Detection and Matching. Computer Vision
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Seminar paper from the year 2020 in the subject Engineering - Computer Engineering, grade: 1,0, University of Applied Sciences Ulm, language: English, abstract: This thesis deals with the eminent as well as demanding subfield of computer vision for the implementation of image processing and image analysis processes. Explicitly meant here is the research field of 'Feature Detection and Matching'. In concrete terms, this field of research comprises numerous proven and tested detection algorithms for the calculation of abstract image information as well as for local decision making at image points for feature recognition.The tangible application of this form of technology takes place in many sub-competencies of computer vision. These include the joining of image mosaics, image and video stabilization, and the recognition and/or match analysis of image object instances.There are two main principles of feature recognition: Feature Matching, describes the viewing and recognition of all features within an image object and the assignment of these based on their local features, feature Tracking, describes the analysis of image features with local search techniques, such as correlation, to find and track image features.The main goal of the scientific work requires the definition and explanation of essential features of the applied methodologies in a manageable abstract form. In doing so, numerous recognized fields of computer vision and applied mathematics are included for the purpose of argumentation and proof. Of elementary importance is the constant attempt to show a smooth transition between concepts that are particularly theoretically mathematically based and the actual practical application and use. At this point, numerous specially developed software elements in Python are used with the OpenCV library to illustrate the practical part.The main source of this scientific work is the extensive book 'Computer Vision: Algorithms and Applications' by Richard Szeliski as well as all other scientific papers of the experts listed in his book.The completion of this thesis is accompanied by a self-developed software, which uses the discussed methods for feature detection and matching to perform image processing and image analysis processes. Artikel-Nr. 9783346347657
Neu kaufen
EUR 17,95
EUR 60,28 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 1 verfügbar