Tissue characterization by combination of mathematical morphology and texture analysis: A new method for recognition of rejection after heart transplantation

1992 ◽  
Vol 14 (2) ◽  
pp. 210-211
Author(s):  
E Lieback
Keyword(s):  
Heart Transplantation ◽  
Texture Analysis ◽  
Mathematical Morphology ◽  
Tissue Characterization ◽  
New Method

Ultrasonic Tissue Characterization By Texture Analysis: Elimination Of Tissue-Independent Factors

1987 ◽  
Author(s):  
Dieter Schlaps ◽  
Ivan Zuna ◽  
Michael Walz ◽  
Jochen Volk ◽  
Ulrich Rath ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Tissue Characterization

Image Retrieval Based on Edge Detection and Histogram

2012 ◽  
Vol 157-158 ◽  
pp. 1038-1041
Author(s):  
Wei Dong ◽  
Yan Dong Tang
Keyword(s):  
Edge Detection ◽  
Image Retrieval ◽  
Mathematical Morphology ◽  
Paper Analysis ◽  
Experimental Results ◽  
New Method

Based on the existing algorithm, improved mathematical morphology for image retrieval, a new method, using the combination of edge magnitude histogram and edge angular histogram, was proposed in this paper. Analysis and experimental results reveal that the proposed algorithm has a superior image retrieving performance.

scholarly journals A new method for vehicles detection and tracking using information and image processing

2021 ◽  
Vol 11 (6) ◽  
pp. 4942
Author(s):  
Mazouzi Amine ◽  
Kerfa Djoudi ◽  
Ismail Rakip Karas
Keyword(s):  
Image Processing ◽  
Mathematical Morphology ◽  
New Method ◽  
Video Sequences ◽  
Detection Level ◽  
Low Level ◽  
Detection And Tracking ◽  
High Level

<span lang="EN-US">In this article, a new method of vehicles detecting and tracking is presented: A thresholding followed by a mathematical morphology treatment are used. The tracking phase uses the information about a vehicle. An original labeling is proposed in this article. It helps to reduce some artefacts that occur at the detection level. The main contribution of this article lies in the possibility of merging information of low level (detection) and high level (tracking). In other words, it is shown that many artefacts resulting from image processing (low level) can be detected, and eliminated thanks to the information contained in the labeling (high level). The proposed method has been tested on many video sequences and examples are given illustrating the merits of our approach.</span>

Method for Determining Texture Parameters of Processed Precision Surfaces by Correlation

2019 ◽  
Vol 822 ◽  
pp. 731-736
Author(s):  
Aleksei Abramov ◽  
Sergej M. Bobrovskij ◽  
Nikolay Nosov ◽  
Vladimir Tabakov ◽  
Fanyusa Lopatina
Keyword(s):  
Texture Analysis ◽  
Russian Federation ◽  
State Standards ◽  
Comparative Assessment ◽  
The State ◽  
New Method ◽  
Texture Parameters ◽  
The Russian Federation ◽  
Autocorrelation Method ◽  
Machined Surfaces

The article describes a new method for texture analysis of precision machined surfaces, which is based on the use of computer optics and an autocorrelation method for processing the obtained images of the textures of the studied microreliefs. The method is based on a probabilistic comparative assessment of the unknown texture of the studied microrelief with known textures of the reference microreliefs, for which the parameters of the microreliefs are predetermined according to the state standards of the Russian Federation.

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