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Visual image feature extraction and matching method based on ORB and active vision

An image feature extraction, active vision technology, applied in character and pattern recognition, instrument, calculation and other directions, can solve the EKF dimension disaster and other problems, achieve the effect of shortening the operation time, meeting real-time performance, and good real-time performance

Active Publication Date: 2017-05-31
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

In the document "Improving computational and memory requirements of simulation and mapbuilding algorithms", it is pointed out that for EKF-SLAM with full state estimation, the number of feature points continues to increase, which will bring dimensionality disaster to EKF

Method used

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  • Visual image feature extraction and matching method based on ORB and active vision
  • Visual image feature extraction and matching method based on ORB and active vision
  • Visual image feature extraction and matching method based on ORB and active vision

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Embodiment

[0035] For the convenience of description, the relevant technical terms appearing in the specific implementation are explained first:

[0036] ORB (Oriented Brief) comes from the article "ORB: an efficient alternative to SIFT orSURF", which is a new corner detection and feature description algorithm.

[0037] figure 1 It is a flow chart of the visual image feature extraction and matching method based on ORB and active vision in the present invention.

[0038] In this embodiment, the experimental images are image sequences of the surface of cardiac soft tissue collected by a monocular endoscope. The image sequence resolution is 320×240, and 30 frames of images are taken per second. The internal parameters of the endoscope are: f u =530.9003,f v =581.00362, u 0 =136.63037, v 0 =161.32884,k 1 =-0.2865,k 2 = 0.29524. The hardware and software environment used in the experiment is: Intel(R) Core(TM) i5-2450M@2.5GHz, memory 4G, Windows 7 system, and implemented in MATLAB 201...

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Abstract

The invention discloses a visual image feature extraction and matching method based on ORB and active vision. The method comprises steps of using highly-efficient rapid ORB feature extraction algorithm to extract feature parameters; using a probability statistical method to calculate distribution indexes of regional features; under the premise of ensuring uniform distribution of feature points, selecting a certain number of feature points according to the probability, and by combining principles and application of active vision, calculating interested ellipse searching domains; and using the nearest neighbor matching algorithm and the RANSAC algorithm to obtain uniformly distributed map feature points with stable numbers. The method is characterized by simple calculation, good matching effects and ability of meeting requirements of system timeliness.

Description

technical field [0001] The invention belongs to the technical field of computer vision image processing, and more specifically relates to a visual image feature extraction and matching method based on ORB and active vision. Background technique [0002] Simultaneous localization and mapping (SLAM) is an important research content of autonomous robot navigation. Its purpose is to estimate the trajectory of the robot and the location of environmental landmarks in a full state while the robot is moving. At present, in terms of algorithms, there are mainly two methods, EKF-SLAM and particle filter-based SLAM. In terms of sensing methods, visual SLAM has gradually become the mainstream in SLAM research due to the advantages of convenient feature extraction, large amount of information, and low cost of visual sensors. [0003] Feature extraction and matching are two important issues in SLAM. The number of features extracted by the feature extraction algorithm and the position di...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/462G06V10/757
Inventor 刘珊郑文锋曾庆川杨波李晓璐彭小羽
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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