JOURNAL ARTICLE

<title>Morphological theory in image feature extraction</title>

Feng GuiQiwei Lin

Year: 2003 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 4898 Pages: 247-251   Publisher: SPIE

Abstract

As we known that morphology is the technique that based upon set theory and it can be used for binary image processing and gray image processing. The principle and the geometrical meaning of morphological boundary detecting for image were discussed in this paper, and the selecting of structure element was analyzed. Comparison was made between morphological boundary detecting and traditional boundary detecting method, conclusion that morphological boundary detecting method has better compatibility and anti-interference capability was reached. The method was also used for L.V. cineangiograms processing. In this paper we hoped to build up a foundation for automatic detection of L.V. contours based on the features of L.V. cineangiograms and Morphological theory, for the further study of L.V. wall motion abnormalities, because wall motion abnormalities of L.V. due to myocardia ischeamia caused by coronary atherosclerosis is a significant feature of Atherosclerotic coronary heart disease (CHD). An algorithm that based on morphology for L.V. contours extracting was developed in this paper.

Keywords:
Mathematical morphology Artificial intelligence Computer science Feature extraction Boundary (topology) Computer vision Image processing Binary image Pattern recognition (psychology) Binary number Gray level Feature (linguistics) Image (mathematics) Algorithm Mathematics Mathematical analysis Arithmetic

Metrics

3
Cited By
0.00
FWCI (Field Weighted Citation Impact)
3
Refs
0.12
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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