Active Contours Using Harmonic Global Division Function

M T Bhatti,S Soomro,A M Bughio,A Anwar,M A Soomro,T A Soomro

doi:10.48084/etasr.2866

Abstract

This paper presents the region-based active contours method based on the harmonic global signed pressure force (HGSPF) function. The proposed formulation improves the performance of the level set method by utilizing intensity information based on the global division function, which has the ability to segment out regions with higher intensity differences. The new energy utilizes harmonic intensity, which can better preserve the low contrast details and can segment complicated areas easily. A Gaussian kernel is adjusted to regularize level set and to escape an expensive reinitialization. Finally, a set of real and synthetic images are used for validation of the proposed method. Results demonstrate the performance of the proposed method, the accuracy values are compared to previous state-of-the-art methods.

Highlights

Segmentation is a technique to isolate particular image regions having a variety of uses in image processing and computer vision [1]
Active contour image segmentation is a strategy, in which an implicit curve is deformed using some minimization procedure until it achieves the ideal boundary
Motivated by [7, 8, 15], we propose a novel harmonic global signed pressure force (HGSPF) function

Summary

Introduction

Segmentation is a technique to isolate particular image regions having a variety of uses in image processing and computer vision [1]. The work in [9] is viewed as the most utilized model for global region based segmentation This strategy is not suitable for unclear boundaries and images which have intense pixel contrast and complicated background variations. To minimize such problems, authors in [8] proposed an altered global region based technique, which utilizes four intensity means for pixel regions across the image. Authors in [7] proposed a strategy which utilizes global pixel data from [9] and builds up a SPF (Signed Pressure Force) function. HGSPF function utilizes global division and harmonic intensity information in its design It yields better results over images having complicated intensity information and/or low contrast. The results are compared in terms of accuracy, which indicates the effectiveness of the proposed method compared to previous state of the art methods

Methods

Results

Conclusion