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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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Book ChapterDOI

An approach for the automatic cephalometric landmark detection using mathematical morphology and active appearance models

TL;DR: Results show that AAM combined with mathematical morphology is the suitable method for clinical cephalometric applications.
Journal ArticleDOI

Non-parametric and region-based image fusion with Bootstrap sampling

TL;DR: A non-parametric and region-based image fusion based on the Bootstrap sampling (BS) principle, which reduces the dependence effect of pixels in real images and minimizes the fusion time.
Proceedings ArticleDOI

Adaptive image retrieval using a Graph model for semantic feature integration

TL;DR: How semantic relations between multimedia objects based on user interaction can be learnt and then integrated with visual and textual features into a unified framework is described and ideas to implement short-term learning from relevance feedback are presented.
Proceedings ArticleDOI

Classification of breast MRI lesions using a backpropagation neural network (BNN)

TL;DR: Preliminary results show an area under the ROC curve for the testing stage equals to 0.913, illustrating the promise of using BNN as a physician's assistant for breast MRI classification.