ECG Image Features Extraction

Alaa Aldine Mahmood, Khalid

	ECG Image Features Extraction
Baghdad College of Economic sciences University
Article 1, Volume 0, Issue 37, 2018, Pages 326-341
Author
Khalid Alaa Aldine Mahmood
Abstract
In recent time the availability of ECG image resources on the world has increased tremendously. This has created a demand for effective and flexible techniques for automatic ECG image features extraction. That can assisted the traditional techniques that still depending on the human experts , that it may be suffer from some problems that made it inefficient in this issue , therefore ; one needs to develop techniques in order to increase efficiency and effectiveness of ECG image features extraction by analyzing ECG wave image and extracting the visual content of these images . One of these techniques is the content base image retrieval which is an efficient way for retrieving images features from the image database automatically based on their visual contents. In this paper a software system are designed and implemented to detect normal ECG image features by extracting features from the digital binary ECG image by applying two methods that are: (1) Histogram detection method which detect image using a histogram that extracted by performing histogram Run Length Coding (RLC) generation operations. (2) Contour detection method which detected images using (The prominent edge point) of the images that extracted using boundary detection. Q, R, S, and T peaks features are carried out between the three digital ECG wave image. The results show that the proposed software system is robust and works depending on a good enhanced binary ECG wave image.
Keywords
ECG; Image enhancement; Image Processing; Image restoration; Image Features; Edge Detection; and RLC; RLC

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