Feature Classification in Ultrasound Textures for Image Quality Assessment:a Preliminary Study on the Characterization and Selection of Haralick Parameters by Means of Correlation Matrices |
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| L. Schinaia, A. Scorza , F. Orsini,S. A. Sciuto |
- Abstract:
- This paper describes a preliminary study on feature selection from the gray level co-occurrence matrix (GLCM) among the 14 features proposed by R.M. Haralick (1979) with the aim to apply them to ultrasound image classification and Quality Assessment. In particular4 main-classes of images with different patterns (Lines, Chess, alternates Row and Circles)have been implemented and different levels ofspeckle noisehave been added to simulate ultrasound images with different textures.With the aim to characterize therelationship betweenHaralickfeatures and the pattern type, size, contrastand noise, someCorrelation Matrices have been implemented. Preliminary results are explained and discussed.
- Keywords:
- diagnostic ultrasound, Haralick textural features, uniformity, B-mode, quality assessment
- Download:
- IMEKO-TC4-2017-032.pdf
- DOI:
- -
- Event details
- IMEKO TC:
- TC4
- Event name:
- TC4 Symposium 2017
- Title:
22nd IMEKO TC4 Symposium and 20th International Workshop on ADC Modelling and Testing
"Supporting world development through electric&electronic measurements"- Place:
- Iasi, ROMANIA
- Time:
- 14 September 2017 - 15 September 2017