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Active Contour Model in Deep Learning Era: A Revise and Review

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Applications of Hybrid Metaheuristic Algorithms for Image Processing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 890))

Abstract

Active Contour (AC)-based segmentation has been widely used to solve many image processing problems, specially image segmentation. While these AC-based methods offer object shape constraints, they typically look for strong edges or statistical modeling for successful segmentation. Clearly, AC-based approaches lack a way to work with labeled images in a supervised machine learning framework. Furthermore, they are unsupervised approaches and strongly depend on many parameters which are chosen by empirical results. Recently, Deep Learning (DL) has become the go-to method for solving many problems in various areas. Over the past decade, DL has achieved remarkable success in various artificial intelligence research areas. DL is supervised methods and requires large volume ground-truth. This paper first provides a fundamental of both Active Contour techniques and Deep Learning framework. We then present the state-of-the-art approaches of Active Contour techniques incorporating in Deep Learning framework.

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Authors and Affiliations

  1. Department of Computer Science and Computer Engineering, University of Arkansas, Fayetteville, AR, 72701, USA

    T. Hoang Ngan Le, Khoa Luu & Kyle Sadler

  2. Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada

    Chi Nhan Duong & Kha Gia Quach

  3. Department of Computer Science, University of Science, Ho Chi Minh, Vietnam

    Thanh Dat Truong

  4. Department of Electrical and Computer Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA

    Marios Savvides

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  1. T. Hoang Ngan Le
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Correspondence to T. Hoang Ngan Le .

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  1. CUCEI, University of Guadalajara, Guadajalara, Mexico

    Diego Oliva

  2. CUCEI, University of Guadalajara, Guadajalara, Mexico

    Salvador Hinojosa

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Hoang Ngan Le, T. et al. (2020). Active Contour Model in Deep Learning Era: A Revise and Review. In: Oliva, D., Hinojosa, S. (eds) Applications of Hybrid Metaheuristic Algorithms for Image Processing. Studies in Computational Intelligence, vol 890. Springer, Cham. https://doi.org/10.1007/978-3-030-40977-7_11

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