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Edge detection
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#	Item
41	Detecting Object Boundaries Using Low-, Mid-, and High-level Information Songfeng Zheng Zhuowen Tu Alan Yuille Add to Reading List Source URL: pages.ucsd.edu Language: English - Date: 2007-03-18 16:52:36 Feature detection Computer vision Ensemble learning Image processing Shape context Image segmentation Canny edge detector Edge detection AdaBoost Thresholding Boosting Classifier
42	Fast Feature Detection and Stochastic Parameter Estimation of Road Shape using Multiple LIDAR Kevin Peterson, Jason Ziglar, and Paul E. Rybski The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 Add to Reading List Source URL: www.ri.cmu.edu Language: English - Date: 2008-12-02 20:27:00 Feature detection Signal processing Functional analysis Image processing Fourier analysis Lidar Wavelet Velodyne Inc. Convolution Curb Edge detection Radar
43	Two thresholds are better than one Add to Reading List Source URL: www.vast.uccs.edu Language: English - Date: 2010-10-23 12:03:50 Image processing Feature detection Psychometrics Image segmentation Thresholding Canny edge detector Edge detection Threshold Background subtraction Statistical hypothesis testing
44	© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promo Add to Reading List Source URL: www.wjscheirer.com Language: English - Date: 2011-12-05 18:03:14 Face recognition Feature detection Image processing Face detection Facial recognition system Template matching Image segmentation FERET Pattern recognition Canny edge detector KadirBrady saliency detector
45	Local Blur Estimation and Super-Resolution Ming-Chao Chiang Terrance E. Boult Columbia University Add to Reading List Source URL: www.vast.uccs.edu Language: English - Date: 2003-12-24 21:58:15 Image processing Super-resolution imaging Edge detection Conference on Computer Vision and Pattern Recognition Gaussian blur Image scaling Deblurring Algorithm
46	Project 3 Filter 2.1 This filter is pretty straightforward. All it has to do is invert the color of each pixel in the selected area. You should invert each of the red, green, and blue channels Add to Reading List Source URL: cs.brown.edu Language: English - Date: 2015-09-02 15:51:30 Image processing Feature detection Gaussian function Signal processing Filter theory Gaussian blur Bilateral filter Edge detection Filter Kernel Image scaling Photographic filter
47	Cross-Field Joint Image Restoration via Scale Map Qiong Yan§ Xiaoyong Shen§ Li Xu§ Xiaopeng Zhang† Liang Shen† Add to Reading List Source URL: www.cse.cuhk.edu.hk Language: English - Date: 2013-09-27 19:04:02 Image processing Feature detection Edge detection Image gradient
48	Physical Panoramic Pyramid and Noise Sensitivity in Pyramids Weihong Yin and Terrance E. Boult Electrical Engineering and Computer Science Department Lehigh University, Bethlehem, PAAbstract Multi-resolution techn Add to Reading List Source URL: www.vast.uccs.edu Language: English - Date: 2005-11-27 17:27:09 Image processing Digital photography Signal processing Digital signal processing Feature detection Pyramid Speeded up robust features Image noise Noise Edge detection Omnidirectional camera Digital camera
49	c °2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution Add to Reading List Source URL: thomas.deselaers.de Language: English - Date: 2014-10-11 09:29:38 Image processing Image segmentation Image gradient Edge detection Pixel Shape context