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research-article

Adaptive artistic stylization of images

Authors:

Ameya Deshpande,

Shanmuganathan RamanAuthors Info & Claims

ICVGIP '16: Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing

Article No.: 3, Pages 1 - 8

https://doi.org/10.1145/3009977.3009985

Published: 18 December 2016 Publication History

Abstract

In this work, we present a novel non-photorealistic rendering method which produces good quality stylization results for color images. The procedure is driven by saliency measure in the foreground and the background region. We start with generating saliency map and simple thresholding based segmentation to get rough estimation of the foreground-background mask. We improve this mask by using a scribble-based method where the scribbles for foreground-background regions are automatically generated from the previous rough estimation. Followed by the mask generation, we proceed with an iterative abstraction process which involves edge-preserving blurring and edge detection. The number of iterations of the abstraction process to be performed in the foreground and background regions are decided by tracking the changes in saliency measure in the foreground and the background regions. Performing unequal number of iterations helps to improve the average saliency measure in more salient region (foreground) while decreasing the average saliency measure in the non-salient region (background). Implementation results of our method shows the merits of this approach with other competing methods.

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Cited By

Kumar MPoornima BNagendraswamy HManjunath C(2021)Structure-preserving NPR framework for image abstraction and stylizationThe Journal of Supercomputing10.1007/s11227-020-03547-wOnline publication date: 21-Jan-2021
https://doi.org/10.1007/s11227-020-03547-w
Kumar MPoornima BNagendraswamy HManjunath C(2019)A comprehensive survey on non-photorealistic rendering and benchmark developments for image abstraction and stylizationIran Journal of Computer Science10.1007/s42044-019-00034-12:3(131-165)Online publication date: 3-May-2019
https://doi.org/10.1007/s42044-019-00034-1

Index Terms

Adaptive artistic stylization of images
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Image processing
      2. Image-based rendering
    2. Rendering
      1. Non-photorealistic rendering

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Published In

cover image ACM Other conferences

ICVGIP '16: Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing

December 2016

743 pages

ISBN:9781450347532

DOI:10.1145/3009977

Program Chairs:
Dhruv Batra
Georgia Tech
,
Michael Brown
York University, Canada
,
Vijay Natarajan
Indian Institute of Science, Bangalore

Copyright © 2016 ACM.

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Google Inc.
QI: Qualcomm Inc.
Tata Consultancy Services
NVIDIA
MathWorks: The MathWorks, Inc.
Microsoft Research: Microsoft Research

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 December 2016

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ICVGIP '16

Sponsor:

QI
MathWorks
Microsoft Research

ICVGIP '16: Indian Conference on Computer Vision, Graphics and Image Processing

December 18 - 22, 2016

Assam, Guwahati, India

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ICVGIP '16 Paper Acceptance Rate 95 of 286 submissions, 33%;

Overall Acceptance Rate 95 of 286 submissions, 33%

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Cited By

Kumar MPoornima BNagendraswamy HManjunath C(2021)Structure-preserving NPR framework for image abstraction and stylizationThe Journal of Supercomputing10.1007/s11227-020-03547-wOnline publication date: 21-Jan-2021
https://doi.org/10.1007/s11227-020-03547-w
Kumar MPoornima BNagendraswamy HManjunath C(2019)A comprehensive survey on non-photorealistic rendering and benchmark developments for image abstraction and stylizationIran Journal of Computer Science10.1007/s42044-019-00034-12:3(131-165)Online publication date: 3-May-2019
https://doi.org/10.1007/s42044-019-00034-1

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