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From Image to Data Using Common ImageāProcessing Techniques
- Source :
- Current Protocols in Cytometry
- Publication Year :
- 2010
- Publisher :
- Wiley, 2010.
-
Abstract
- A digital microscopy image is an array of number values, which with adequate contrast can be interpreted as spatial information. Through processing and analysis by mathematical means, using computer-assisted imaging software programs, raw image data contrast can be enhanced to improve the extraction of image features for measurement and analysis. This mathematical feature extraction (referred to as segmentation) provides the basis for general image processing. The methods discussed in this unit address common image analysis challenges such as object counting with touching objects, objects within other objects, and object identification in a field with uneven illumination or uneven brightness, along with step-by-step procedures for achieving these results.
- Subjects :
- Histology
Computer science
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Top-hat transform
Image processing
Biochemistry
Automation
Image texture
Digital image processing
Image Processing, Computer-Assisted
Computer vision
Image Cytometry
Feature detection (computer vision)
Electronic Data Processing
Microscopy
Standard test image
Computers
business.industry
Binary image
General Medicine
Models, Theoretical
Medical Laboratory Technology
Calibration
Artificial intelligence
business
Algorithms
Software
Subjects
Details
- ISSN :
- 19349300 and 19349297
- Volume :
- 54
- Database :
- OpenAIRE
- Journal :
- Current Protocols in Cytometry
- Accession number :
- edsair.doi.dedup.....382ec6e943da876f5ef9ce38aa5cd11d