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Comparative analysis and implementation of structured edge active contour

Shah, Brijesh N.Bhalani, Jaymin K.
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 April 2020
DOI10.11591/ijece.v10i2.pp1842-1848

Abstrak

This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image.In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared.It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.

Kata Kunci

Image Processingactive contourdifference of gaussian (DOG)image segmentationlinear structure tensor

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Comparative analysis and implementation of structured edge active contour | International Journal of Electrical and Computer Engineering (IJECE) | Publiora