Open AccessBook
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.read more
Citations
More filters
Journal ArticleDOI
Linear structures in mammographic images: detection and classification
TL;DR: Methods for detecting linear structures in mammograms, and for classifying them into anatomical types (vessels, spicules, ducts, etc), have potentially wide application in improving the specificity of abnormality detection by exploiting additional anatomical information.
Journal ArticleDOI
Experimental Demonstration of Feature Extraction and Dimensionality Reduction Using Memristor Networks
TL;DR: It is experimentally demonstrated that memristor arrays can be used to perform principal component analysis, one of the most commonly used feature extraction techniques, through online, unsupervised learning.
Journal ArticleDOI
A feature-based approach to conflation of geospatial sources
TL;DR: A graph theoretic approach is used to model the geographic context and to determine the matching features from multiple sources in a Geographic Information System populated with disparate data sources.
Journal ArticleDOI
Feature Extraction With Deep Neural Networks by a Generalized Discriminant Analysis
TL;DR: The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion and displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection.
Book
The Image Processing Handbook, Fourth Edition
TL;DR: This revision of the established standard acts as a singular resource for professionals in the medical, biological, and materials sciences as well as a range of engineering venues, including electrical and computer engineering, optical engineering, telecommunications, and artificial intelligence.