A NOVEL ALGORITHM FOR SPEEDING UP KEYPOINT DETECTION AND MATCHING

2008 ◽  
Vol 08 (04) ◽  
pp. 643-661 ◽  
Author(s):  
JING LI ◽  
TAO YANG ◽  
QUAN PAN ◽  
YONG-MEI CHENG ◽  
JUN HOU
Keyword(s):  
Scale Space ◽  
Feature Detector ◽  
Keypoint Detection ◽  
Invariant Feature ◽  
Illumination Changes ◽  
Speed Up ◽  
Application Fields ◽  
Real Time Application ◽  
Keypoint Detector ◽  
Novel Algorithm

This work proposes a novel keypoint detector called QSIF (Quality and Spatial based Invariant Feature Detector). The primary contributions include: (1) a multilevel box filter is used to build the image scales efficiently and precisely, (2) by examining pixels in quality and spatial space simultaneously, QSIF can directly locate the keypoints without scale space extrema detection in the entire image spatial space, (3) QSIF can precisely control the number of output keypoints while maintaining almost the same repeatability of keypoint detection. This characteristic is essential in many real-time application fields. Extensive experimental results with images under scale, rotation, viewpoint and illumination changes demonstrate that the proposed QSIF has a stable and satisfied repeatability, and it can greatly speed up the keypoint detect and matching.

scholarly journals Keypoint Detection in RGBD Images Based on an Anisotropic Scale Space

2016 ◽  
Vol 18 (9) ◽  
pp. 1762-1771 ◽  
Author(s):  
Maxim Karpushin ◽  
Giuseppe Valenzise ◽  
Frederic Dufaux
Keyword(s):  
Scale Space ◽  
Keypoint Detection

A biologically inspired scale-space for illumination invariant feature detection

2013 ◽  
Vol 24 (7) ◽  
pp. 074024 ◽  
Author(s):  
Vasillios Vonikakis ◽  
Dimitrios Chrysostomou ◽  
Rigas Kouskouridas ◽  
Antonios Gasteratos
Keyword(s):  
Feature Detection ◽  
Scale Space ◽  
Biologically Inspired ◽  
Illumination Invariant ◽  
Invariant Feature

Ocean Surface Rendering Method Based on Mild-Slope Equation

2014 ◽  
Vol 1064 ◽  
pp. 197-204
Author(s):  
Zhuo Yu ◽  
Li Xiong ◽  
Feng Shang
Keyword(s):  
Real Time ◽  
Physical Method ◽  
Ocean Surface ◽  
Process Unit ◽  
Surface Rendering ◽  
Mild Slope Equation ◽  
Calculation Process ◽  
Speed Up ◽  
Real Time Applications ◽  
Real Time Application

Mild-slope equation is usually used in many simulation applications. The equation has obviously benefit which based on physical method that can present the real status of water, but the shortcoming is also clearly that the calculations spending lots of times which not support some real-time applications. We use hyperbola to simple the equation calculation process, and use alternating directions implicit (ADI) way to solve this equation. The result shows that the ADI way can use less calculation and less time to accomplish the calculation. We also use the new features of GPU(graphics process unit) to speed up the calculation so that we can render the surface in real-time application.

scholarly journals Neuromorphic Configurable Architecture for Robust Motion Estimation

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Guillermo Botella ◽  
Manuel Rodríguez ◽  
Antonio García ◽  
Eduardo Ros
Keyword(s):  
Visual System ◽  
Motion Estimation ◽  
Optical Flow ◽  
Visual Motion ◽  
Specific Model ◽  
Biologically Inspired ◽  
Visual Motion Perception ◽  
Illumination Changes ◽  
And Performance ◽  
Application Fields

The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM). This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

A Novel Registration Approach for Mammograms Based on SIFT and Graph Transformation

2012 ◽  
Vol 157-158 ◽  
pp. 1313-1319
Author(s):  
Yang Jun Zhong ◽  
Qian Cai
Keyword(s):  
Breast Cancer ◽  
Graph Transformation ◽  
Scale Invariant ◽  
Invariant Feature ◽  
Feature Transform ◽  
Transformation Methods ◽  
Scale Invariant Feature ◽  
Mammogram Images ◽  
Image Performance ◽  
Novel Algorithm

Mammogram registration is an important step in the processing of automatic detection of breast cancer. It provides aid to better visualization correspondence on temporal pairs of mammograms. This paper presents a novel algorithm based on SIFT feature and Graph Transformation methods for mammogram registration. First, features are extracted from the mammogram images by scale invariant feature transform (SIFT) method. Second, we use graph transformation matching (GTM) approach to obtain more accurate image information. At last, we registered a pair of mammograms using Thin-Plate spline (TPS) interpolation based on corresponding points on the two breasts, and acquire the mammogram registration image. Performance of the proposed algorithm is evaluated by three criterions. The experimental results show that our method is accurate and closely to the source images.

Sign in / Sign up

Export Citation Format

Share Document