Object Detection in Real Images
by Dilip K. Prasad
Publisher: arXiv 2013
Number of pages: 123
We propose a new object detection/recognition method, which improves over the existing methods in every stage of the object detection/recognition process. In addition to the usual features, we propose to use geometric shapes, like linear cues, ellipses and quadrangles, as additional features.
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by David Marshall - Cardiff School of Computer Science
From the table of contents: Image Acquisition: 2D Image Input, 3D imaging; Image processing: Fourier Methods, Smoothing Noise; Edge Detection; Edge Linking; Segmentation; Line Labelling; Relaxation Labelling; Optical Flow; Object Recognition.
by Asim Bhatti (ed.) - InTech
The topics covered in this book include fundamental theoretical aspects of robust stereo correspondence estimation, novel and robust algorithms, hardware implementation for fast execution, neuromorphic engineering, probabilistic analysis, etc.
by Aapo Hyvarinen, Jarmo Hurri, Patrik O. Hoyer - Springer
Introductory textbook and a research monograph on modelling the statistical structure of natural images. The statistical structure of natural images is described using a number of statistical models whose parameters are estimated from image samples.
by Joachim Weickert - Teubner
Many recent techniques for digital image enhancement and multiscale image representations are based on nonlinear PDEs. This book gives an introduction to the main ideas behind these methods, and it describes in a systematic way their foundations.