A Proposed Pipelined-Architecture for FPGA-Based Affine-Invariant Feature Detectors

2006 ◽  
Author(s):  
C. Cabani ◽  
W.J. MacLean
Keyword(s):  
Affine Invariant ◽  
Pipelined Architecture ◽  
Feature Detectors ◽  
Invariant Feature

Distortion calibrating method of measuring rail profile based on local affine invariant feature descriptor

Measurement ◽  
2017 ◽  
Vol 110 ◽  
pp. 11-21 ◽  
Author(s):  
Chao Wang ◽  
Ziji Ma ◽  
Yanfu Li ◽  
Jiuzhen Zeng ◽  
Tan Jin ◽  
...  
Keyword(s):  
Feature Descriptor ◽  
Affine Invariant ◽  
Invariant Feature

scholarly journals Evaluation of Local Feature Detectors for the Comparison of Thermal and Visual Low Altitude Aerial Images

2018 ◽  
Vol 68 (5) ◽  
pp. 473-479 ◽  
Author(s):  
Divya Lakshmi Krishnan ◽  
Rajappa Muthaiah ◽  
Anand Madhukar Tapas ◽  
Krithivasan Kannan
Keyword(s):  
State Of The Art ◽  
Ground Truth ◽  
Local Features ◽  
The State ◽  
Aerial Images ◽  
Affine Invariant ◽  
Atmospheric Conditions ◽  
Spectral Correlation ◽  
Feature Detectors ◽  
Image Pairs

Local features are key regions of an image suitable for applications such as image matching, and fusion. Detection of targets under varying atmospheric conditions, via aerial images is a typical defence application where multi spectral correlation is essential. Focuses on local features for the comparison of thermal and visual aerial images in this study. The state of the art differential and intensity comparison based features are evaluated over the dataset. An improved affine invariant feature is proposed with a new saliency measure. The performances of the existing and the proposed features are measured with a ground truth transformation estimated for each of the image pairs. Among the state of the art local features, Speeded Up Robust Feature exhibited the highest average repeatability of 57 per cent. The proposed detector produces features with average repeatability of 64 per cent. Future works include design of techniques for retrieval of corresponding regions.

Improved Locality affine-invariant feature matching

2021 ◽  
Author(s):  
Yiyuan He ◽  
Nanqing Xia ◽  
Xingsi Liu ◽  
Min Xia
Keyword(s):  
Feature Matching ◽  
Affine Invariant ◽  
Invariant Feature

Equi-affine differential invariants for invariant feature point detection

2019 ◽  
Vol 31 (2) ◽  
pp. 277-296
Author(s):  
STANLEY L. TUZNIK ◽  
PETER J. OLVER ◽  
ALLEN TANNENBAUM
Keyword(s):  
Feature Point ◽  
Image Feature ◽  
Differential Invariants ◽  
Feature Points ◽  
Affine Invariant ◽  
Moving Frames ◽  
Feature Detectors ◽  
Point Detection ◽  
Point Detector ◽  
Method Of Moving Frames

Image feature points are detected as pixels which locally maximise a detector function, two commonly used examples of which are the (Euclidean) image gradient and the Harris–Stephens corner detector. A major limitation of these feature detectors is that they are only Euclidean-invariant. In this work, we demonstrate the application of a 2D equi-affine-invariant image feature point detector based on differential invariants as derived through the equivariant method of moving frames. The fundamental equi-affine differential invariants for 3D image volumes are also computed.

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