Automatic recognition of complete palynomorphs in digital images

2009 ◽  
Vol 22 (1) ◽  
pp. 53-60 ◽  
Author(s):  
J. J. Charles
Keyword(s):  
Digital Images ◽  
Automatic Recognition

scholarly journals Towards automatic recognition of pure & mixed stones using intraoperative endoscopic digital images

2021 ◽  
Author(s):  
Vincent Estrade ◽  
Michel Daudon ◽  
Emmanuel Richard ◽  
Jean‐Christophe Bernhard ◽  
Franck Bladou ◽  
...  
Keyword(s):  
Digital Images ◽  
Automatic Recognition

Automatic recognition of urinary stones: First results from per-operative endoscopic digital images of pure and mixed stones in-situ

2021 ◽  
Vol 79 ◽  
pp. S334-S335
Author(s):  
V. Estrade ◽  
B. Denis De Senneville ◽  
E. Alezra ◽  
G. Capon ◽  
J.C. Bernhard ◽  
...  
Keyword(s):  
Digital Images ◽  
Automatic Recognition ◽  
Urinary Stones ◽  
First Results

scholarly journals Digital Image Automatic Recognition and Tracking Based on Electronic Derotation Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Meirong Gao
Keyword(s):  
Image Recognition ◽  
Digital Image ◽  
Simulation Experiment ◽  
Digital Images ◽  
Social Economy ◽  
Difficult Problem ◽  
Automatic Recognition ◽  
Continuous Development ◽  
Edge Features

With the continuous development of my country’s social economy, the ways to acquire images have become more and more abundant. How to effectively process, manage, and mine images has become a major and difficult problem in research. In view of the difficult problem of image recognition, the electronic derotation algorithm is introduced in this study, by combing and monitoring the edge features, establishing a corresponding sample database, analyzing the edge features of the image, and performing effective and stable tracking, so as to realize the automatic recognition and tracking of the digital image. The simulation experiment results show that the electronic derotation algorithm is effective and can support the automatic recognition and tracking of digital images.

Reduction in size of digital images: does it lead to less detectability or loss of diagnostic information?

1998 ◽  
Vol 27 (2) ◽  
pp. 93-96 ◽  
Author(s):  
C H Versteeg ◽  
G C H Sanderink ◽  
S R Lobach ◽  
P F van der Stelt
Keyword(s):  
Digital Images ◽  
Diagnostic Information

Development of a system for craniofacial analysis from monitor-displayed digital images

1999 ◽  
Vol 28 (2) ◽  
pp. 123-126 ◽  
Author(s):  
E Gotfredsen ◽  
J Kragskov ◽  
A Wenzel
Keyword(s):  
Digital Images

Authentication of Digital Image using Exif Metadata and Decoding Properties

2018 ◽  
pp. 335-341 ◽  
Author(s):  
D. P. Gangwar ◽  
Anju Pathania
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Software Tools ◽  
Robust Analysis

This work presents a robust analysis of digital images to detect the modifications/ morphing/ editing signs by using the image’s exif metadata, thumbnail, camera traces, image markers, Huffman codec and Markers, Compression signatures etc. properties. The details of the whole methodology and findings are described in the present work. The main advantage of the methodology is that the whole analysis has been done by using software/tools which are easily available in open sources.

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