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
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Journal ArticleDOI
Machine vision system: a tool for quality inspection of food and agricultural products
TL;DR: The objective of this paper is to provide in depth introduction of machine vision system, its components and recent work reported on food and agricultural produce.
Journal ArticleDOI
Computational methods for the image segmentation of pigmented skin lesions
Roberta B. Oliveira,Mercedes E. Filho,Zhen Ma,João Paulo Papa,Aledir Silveira Pereira,João Manuel R. S. Tavares +5 more
TL;DR: A review of the current methods for the segmentation of pigmented skin lesions in images, and a comparative analysis with regards to several of the fundamental steps of image processing, such as image acquisition, pre-processing and segmentation.
Journal ArticleDOI
Automated 3-D Segmentation of Lungs With Lung Cancer in CT Data Using a Novel Robust Active Shape Model Approach
TL;DR: A novel robust active shape model (RASM) matching method is utilized to roughly segment the outline of the lungs through an optimal surface finding approach, which delivered statistically significant better segmentation results, compared to two commercially available lung segmentation approaches.
Posted Content
Stochastic Block Models and Reconstruction
TL;DR: Following Decelle et al, this work establishes a rigorous connection between the clustering problem, spin-glass models on the Bethe lattice and the so called reconstruction problem.
Journal ArticleDOI
Obstructive lung diseases: texture classification for differentiation at CT.
TL;DR: The proposed technique discriminates well between patterns of obstructive lung disease on the basis of parenchymal texture alone and was tested with a new cohort of subjects with a similar spectrum of diseases.