scholarly journals Sparse Haar-Like Feature and Image Similarity-Based Detection Algorithm for Circular Hole of Engine Cylinder Head

2018 ◽  
Vol 8 (10) ◽  
pp. 2006
Author(s):  
Wenzhang Zhou ◽  
Yong Chen ◽  
Siyuan Liang
Keyword(s):  
Cylinder Head ◽  
Detection Method ◽  
Detection Algorithm ◽  
Image Similarity ◽  
Matching Accuracy ◽  
Point Matching ◽  
Light Interference ◽  
Engine Cylinder ◽  
Circular Holes ◽  
Feature Point Matching

If the circular holes of an engine cylinder head are distorted, cracked, defective, etc., the normal running of the equipment will be affected. For detecting these faults with high accuracy, this paper proposes a detection method based on feature point matching, which can reduce the detection error caused by distortion and light interference. First, the effective and robust feature vectors of pixels are extracted based on improved sparse Haar-like features. Then we calculate the similarity and find the most similar matching point from the image. In order to improve the robustness to the illumination, this paper uses the method based on image similarity to map the original image, so that the same region under different illumination conditions has similar spatial distribution. The experiments show that the algorithm not only has high matching accuracy, but also has good robustness to the illumination.

scholarly journals Feature Point Matching Method for Aerial Image Based on Recursive Diffusion Algorithm

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 407
Author(s):  
Jiayan Shen ◽  
Xiucheng Guo ◽  
Wenzong Zhou ◽  
Yiming Zhang ◽  
Juchen Li
Keyword(s):  
Large Scale ◽  
High Density ◽  
Feature Point ◽  
Aerial Images ◽  
Image Feature ◽  
Aerial Image ◽  
Experimental Comparison ◽  
Matching Accuracy ◽  
Point Matching ◽  
Feature Point Matching

Aerial images are large-scale and susceptible to light. Traditional image feature point matching algorithms cannot achieve satisfactory matching accuracy for aerial images. This paper proposes a recursive diffusion algorithm, which is scale-invariant and can be used to extract symmetrical areas of different images. This narrows the matching range of feature points by extracting high-density areas of the image and improving the matching accuracy through correlation analysis of high-density areas. Through experimental comparison, it can be found that the recursive diffusion algorithm has more advantages compared to the correlation coefficient method and the mean shift algorithm when matching accuracy of aerial images, especially when the light of aerial images changes greatly.

Vehicle Detection Method under Night Circumstance

2013 ◽  
Vol 380-384 ◽  
pp. 3870-3873 ◽  
Author(s):  
Lin Guo ◽  
Xiang Hui Shen
Keyword(s):  
Difference Method ◽  
Moving Objects ◽  
Detection Method ◽  
Vehicle Detection ◽  
Detection Algorithm ◽  
Intelligent Vehicle ◽  
Urban Street ◽  
Light Interference ◽  
Frame Difference

In intelligent vehicle detection, vehicle detection at night especially detection in the condition of urban street always remains a problem. This paper proposes an effective vehicle detection algorithm. Firstly it extracts effective vehicle edge by the method of embossment which eliminates light interference. Then we detect the vehicle moving area by frame difference method and calculate the threshold by OTSU algorithm. Finally the noise points are removed by erosion and expansion. This method can better extract the moving objects.

Image similarity‐based cardiac rhythm device identification from X‐rays using feature point matching

2021 ◽  
Author(s):  
Akinori Higaki ◽  
Tsukasa Kurokawa ◽  
Takuro Kazatani ◽  
Shinsuke Kido ◽  
Tetsuya Aono ◽  
...  
Keyword(s):  
Cardiac Rhythm ◽  
Feature Point ◽  
Image Similarity ◽  
X Rays ◽  
Point Matching ◽  
Device Identification ◽  
Feature Point Matching

Analysis of Fabric Shape Style Evaluation Method

2014 ◽  
Vol 1048 ◽  
pp. 173-177 ◽  
Author(s):  
Ying Mei Wang ◽  
Yan Mei Li ◽  
Wan Yue Hu
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Evaluation Method ◽  
Contact Method ◽  
Ccd Cameras ◽  
Point Matching ◽  
Feature Point Matching ◽  
Motion Parameters ◽  
Measurement And Evaluation ◽  
Main Factor

Fabric shape style is one of the most important conditions in textile appearance evaluation, and also the main factor influences customer purchasing psychology. At first, the previous fabric shape style evaluation methods are classified and summarized, measurement and evaluation method discussed from tactic and dynamic aspects. Then, companied with computer vision principle, a non-contact method for measuring fabric shape style was put forward. In this method, two high-speed CCD cameras were used to capture fabric movement dynamically, fabric sequences image were obtained in this process. Used the image processing technology include pretreatment and feature point matching to get 3D motion parameters, it can provide data supports for shape style evaluation.

scholarly journals Scene Wireframes Sketching for Drones

Proceedings ◽  
2018 ◽  
Vol 2 (18) ◽  
pp. 1193
Author(s):  
Roi Santos ◽  
Xose Pardo ◽  
Xose Fdez-Vidal
Keyword(s):  
State Of The Art ◽  
Point Clouds ◽  
Outdoor Environment ◽  
Point Matching ◽  
3D Point Clouds ◽  
Complementary Approach ◽  
Straight Line ◽  
Scene Representation ◽  
Feature Point Matching ◽  
3D Scene

The increasing use of autonomous UAVs inside buildings and around human-made structures demands new accurate and comprehensive representation of their operation environments. Most of the 3D scene abstraction methods use invariant feature point matching, nevertheless some sparse 3D point clouds do not concisely represent the structure of the environment. Likewise, line clouds constructed by short and redundant segments with inaccurate directions limit the understanding of scenes as those that include environments with poor texture, or whose texture resembles a repetitive pattern. The presented approach is based on observation and representation models using the straight line segments, whose resemble the limits of an urban indoor or outdoor environment. The goal of the work is to get a full method based on the matching of lines that provides a complementary approach to state-of-the-art methods when facing 3D scene representation of poor texture environments for future autonomous UAV.

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