Skip to Main content Skip to Navigation
Journal articles

SimLocator: robust locator of similar objects in images

Yan Kong 1 Weiming Dong 1 Xing Mei 1 Xiaopeng Zhang 1 Jean-Claude Paul 2 
2 CAD - Computer Aided Design
LIAMA - Laboratoire Franco-Chinois d'Informatique, d'Automatique et de Mathématiques Appliquées, Inria Paris-Rocquencourt
Abstract : Similar objects commonly appear in natural images, and locating and cutting out these objects can be tedious when using classical interactive image segmentation methods. In this paper, we propose SimLocator, a robust method oriented to locate and cut out similar objects with minimum user interaction. After extracting an arbitrary object template from the input image, candidate locations of similar objects are roughly detected by distinguishing the shape and color features of each image. A novel optimization method is then introduced to select accurate locations from the two sets of candidates. Additionally, a mattingbased method is used to improve the results and to ensure that all similar objects are located in the image. Finally, a method based on alpha matting is utilized to extract the precise object contours. To ensure the performance of the matting operation, this work has developed a new method for foreground extraction. Experiments show that SimLocator is more robust and more convenient to use compared to other more advanced repetition detection and interactive image segmentation methods, in terms of locating similar objects in images.
Document type :
Journal articles
Complete list of metadata

Cited literature [23 references]  Display  Hide  Download
Contributor : Weiming Dong Connect in order to contact the contributor
Submitted on : Wednesday, January 29, 2014 - 7:08:39 AM
Last modification on : Friday, February 4, 2022 - 3:10:21 AM
Long-term archiving on: : Sunday, April 9, 2017 - 2:06:20 AM


Files produced by the author(s)




Yan Kong, Weiming Dong, Xing Mei, Xiaopeng Zhang, Jean-Claude Paul. SimLocator: robust locator of similar objects in images. The Visual Computer, Springer Verlag, 2013, 29 (9), pp.861-870. ⟨10.1007/s00371-013-0847-8⟩. ⟨hal-00937938⟩



Record views


Files downloads