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access icon free Co-segmentation of multiple similar images using saliency detection and region merging

  • Author(s): Chongbo Zhou 1, 2  and  Chuancai Liu 1
    • View affiliations
    • Affiliations: 1: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, People's Republic of China;
      2: School of Physics and Engineering, Qufu Normal University, Qufu, Shandong 273165, People's Republic of China
  • Source: Volume 8, Issue 3, June 2014, p. 254 – 261
    DOI:  10.1049/iet-cvi.2012.0266 , Print ISSN 1751-9632, Online ISSN 1751-9640
© The Institution of Engineering and Technology
Received 10/09/2012, Accepted 15/10/2013, Revised 23/08/2013, Published 28/11/2013

The aim of co-segmentation is to simultaneously segment multiple images depicting an identical or similar object. In this study, a co-segmentation method using saliency detection and region merging is proposed. The saliency detection results using different detection methods on different types of colour space are combined to produce seed regions for each image in the image group. The initial seed regions of all the images are refined by eliminating the dissimilar ones to ensure accurate seed regions for each images as possible. Region merging is performed on each image individually in order to allow our method to be applied to large image groups. The maximal similarity measurement and nearest similarity measurement are defined as merging rules. The deliberately designed merging strategy aims to merge two regions using the maximal similarity rule and label two regions as the same class but not merge them using the nearest similarity rule. The proposed method has been compared with some state-of-the-art methods on three datasets, and the experimental results show its effectiveness.

Inspec keywords: image segmentation

Other keywords: nearest similarity measurement; saliency detection; region merging; multiple similar images cosegmentation; maximal similarity measurement

Subjects: Computer vision and image processing techniques; Optical, image and video signal processing

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