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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Book ChapterDOI
The Automated Identification of Tubercle Bacilli using Image Processing and Neural Computing Techniques
TL;DR: A preliminary investigation is presented here, which makes use of image processing techniques and neural network classifiers for the automatic identification of TB bacilli on Auramine stained sputum specimens.
Journal ArticleDOI
Object recognition in construction-site images using 3D CAD-based filtering
TL;DR: A robust image processing methodology to effectively extract the objects of interest from construction-site digital images makes use of advanced imaging algorithms and a three-dimensional computer aided design perspective view to increase the accuracy of the object recognition.
Journal ArticleDOI
A critical review and comparative study on image segmentation-based techniques for pavement crack detection
TL;DR: The most common rule-driven-based and data-driven image segmentation algorithms are compared and discussed in this article , and strategies to obtain better results such as hybrid integration algorithms and optimization methods are presented.
Journal ArticleDOI
Estimation of 3-D pore network coordination number of rocks from watershed segmentation of a single 2-D image
TL;DR: In this paper, the authors used 3D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2D cross-sectional image.
Journal ArticleDOI
Assessment of four neural network based classifiers to automatically detect red lesions in retinal images
TL;DR: The aim of this study was to automatically detect red lesions (RLs), like haemorrhages and microaneurysms, in diabetic retinopathy by extracting a set of colour and shape features from image regions and performing feature selection using logistic regression.