Abstract
AbstractActive contours are used in the image processing application including edge detection, shape modeling, medical image-analysis, detectable object boundaries, etc. Shape is one of the important features for describing an object of interest. Even though it is easy to understand the concept of 2D shape, it is very difficult to represent, define and describe it. In this paper, we propose a new method to implement an active contour model using Daubechies complex wavelet transform combined with B-Spline based on context aware. To show the superiority of the proposed method, we have compared the results with other recent methods such as the method based on simple discrete wavelet transform, Daubechies complex wavelet transform and Daubechies complex wavelet transform combined with B-Spline.
Highlights
Contours are used extensively in image processing applications
We propose a new method to implement an active contour model using Daubechies complex wavelet transform combined with B-Spline based on context-aware (DCWTBCA)
To show the superiority of the proposed method, we have compared the results with the other recent methods such as the method based on simple discrete wavelet transform (DWT), Daubechies complex wavelet transform (DCWT) and Daubechies complex wavelet transform combined with B-Spline (DCWTB)
Summary
Contours are used extensively in image processing applications. Active contours can be classified according to several different criteria. The dual-tree Complex Wavelet Transform (DTCWT) was proposed by Kingsbury [16]. Bharath [17] has presented a framework for the construction of steerable complex wavelet This transform avoids the shortcomings of discrete wavelet transform, but it uses a non-separable and highly redundant implementation. Lawton [18] and Lina [19] used an approximate shift-invariant Daubechies complex wavelet transform for avoiding redundancy and providing phase information. We propose a new method to implement an active contour model using Daubechies complex wavelet transform combined with B-Spline based on context-aware (DCWTBCA). The rest of the paper is organized as follows: in section 2, we described the basic concepts of Daubechies complex wavelet transform.
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