scholarly journals Inspecting Morphological Features of Mosquito Wings for Identification with Image Recognition Tools

2018 ◽  
Author(s):  
Clinton Haarlem ◽  
Rutger Vos
Keyword(s):  
Feature Extraction ◽  
Image Recognition ◽  
Cell Phone ◽  
Low Cost ◽  
Image Feature ◽  
Mitigation Measures ◽  
Disease Vectors ◽  
Image Feature Extraction ◽  
Important Disease ◽  
Common Cell

AbstractMosquitoes are important disease vectors. Different mosquito genera are associated with different diseases at varying levels of specificity. Hence, quick and low-cost methods of identification, even if relatively coarse and to genus level, will be of use in assessing risk and informing mitigation measures. Here we assess the extent to which digital photographs of mosquito wings taken with common cell phone cameras and clip-on lenses can be used to discriminate among mosquito genera when fed into image feature extraction algorithms. Our results show that genera may be distinguished on the basis of features extracted using the SURF algorithm. However, we also found that the naïve features examined here require very standardized photography and that different phone cameras have different signatures that may need to be taken into account.

scholarly journals Slope Collapse Detection Based on Image Processing

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xin-Dai An ◽  
Xiang-Wen Xie ◽  
Di Wu ◽  
Ke-Feng Song
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Image Recognition ◽  
Motion Detection ◽  
Detection Algorithm ◽  
Image Feature ◽  
Moving Targets ◽  
Image Feature Extraction ◽  
Slope Collapse ◽  
River Embankment

In this paper, we study a task of slope collapse detection (SCD) for river embankment and formulate it as the tasks of motion detection and image recognition. Specifically, we introduce an SCD method based on motion detection and image recognition technologies to help inspector attendants detect the slope collapse. In this method, we use the foreground motion detection algorithm to identify the slope collapse of the scene of the river embankment. Since the moving targets in the foreground may not only be the slope collapse but also maybe some biology, we further use the image feature extraction and image recognition technology to recognize the foreground motion area, thus eliminating the influence of the biology on the detection results. Experimental results on the relevant scene data show that the proposed method can identify the slope collapse in real-time, and can effectively eliminate the motion interference of the biology, which has a high practical value.

Study on the Image Process of Wheels Based on Machine Vision

2011 ◽  
Vol 179-180 ◽  
pp. 914-919
Author(s):  
Shi Feng Wang ◽  
Chang Chun Li ◽  
Jing Yu ◽  
Tian Hou Zhang
Keyword(s):  
Feature Extraction ◽  
Machine Vision ◽  
Edge Detection ◽  
Image Recognition ◽  
Image Feature ◽  
Image Process ◽  
Image Feature Extraction ◽  
Image Information ◽  
Industrial Cameras

This paper introducted the machine vision technology into the field of wheel suspension coating, used the industrial cameras for the image information of the wheel center and the valve hole, did the edge detection of the valve hole and the wheel based on visual c++ platform ,making the image feature extraction and analysis, thus completing image recognition of the wheel center and the valve hole, realized hang the wheels to the conveyor of automatically.

Sign in / Sign up

Export Citation Format

Share Document