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Image Processing: Analysis and Machine Vision

TLDR
The digitized image and its properties are studied, including shape representation and description, and linear discrete image transforms, and texture analysis.
Abstract
List of Algorithms. Preface. Possible Course Outlines. 1. Introduction. 2. The Image, Its Representations and Properties. 3. The Image, Its Mathematical and Physical Background. 4. Data Structures for Image Analysis. 5. Image Pre-Processing. 6. Segmentation I. 7. Segmentation II. 8. Shape Representation and Description. 9. Object Recognition. 10. Image Understanding. 11. 3d Geometry, Correspondence, 3d from Intensities. 12. Reconstruction from 3d. 13. Mathematical Morphology. 14. Image Data Compression. 15. Texture. 16. Motion Analysis. Index.

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Journal ArticleDOI

A review of semantic segmentation using deep neural networks

TL;DR: The field of semantic segmentation as pertaining to deep convolutional neural networks is reviewed and comprehensive coverage of the top approaches is provided and the strengths, weaknesses and major challenges are summarized.
Journal ArticleDOI

3-D active appearance models: segmentation of cardiac MR and ultrasound images

TL;DR: The comprehensive design of a three-dimensional (3-D) active appearance model (AAM) is reported for the first time as an involved extension of the AAM framework introduced by Cootes et al.
Journal ArticleDOI

A Survey of Urban Reconstruction

TL;DR: The goal is to provide a survey that will help researchers to better position their own work in the context of existing solutions, and to help newcomers and practitioners in computer graphics to quickly gain an overview of this vast field.
Book

Physical Principles of Remote Sensing

TL;DR: The Global Positioning System (GPS) as mentioned in this paper is a global positioning system for remote sensing that uses electromagnetic signals from the Earth's atmosphere to estimate the position of a target.
Journal ArticleDOI

Lesion border detection in dermoscopy images.

TL;DR: A systematic overview of the recent border detection methods in the literature paying particular attention to computational issues and evaluation aspects is presented.