Paper Info
Title
Detection and segmentation of approximate repetitive patterns in relief images
Abstract
Algorithms for detection of repeating patterns in images often assume that the repetition is regular and highly similar across the instances. Approximate repetitions are also of interest in many domains such as hand carved sculptures, wall decorations, groups of natural objects, etc. Detection of such repetitive structures can help in applications such as image retrieval, image inpainting, 3D reconstruction, etc. In this work, we look at a specific class of approximate repetitions: those in images of hand carved relief structures. We present a robust hierarchical method for detecting such repetitions. Given a single image with reliefs, our algorithm finds dense matches of local features across the image at various scales. The matching features are then grouped based on their geometric configuration to find repeating elements. We also propose a method to group the repeating elements to segment the repetitive patterns in an image. In relief images, foreground and background have nearly the same texture, and matching of a single feature would not provide reliable evidence of repetition. Our grouping algorithm integrates evidences of repetition to reliably find repeating patterns. Input image is processed on a scale-space pyramid to effectively detect all possible repetitions at different scales. Our method has been tested on images with large varieties of complex repetitive patterns and the qualitative results show the robustness of our approach.
Year
DOI
Venue
2012
10.1145/2425333.2425379
ICVGIP
Keywords
Field
DocType
possible repetition,approximate repetitive pattern,relief image,input image,repeating pattern,repeating element,image retrieval,image inpainting,approximate repetition,single image,complex repetitive pattern
Computer vision,Pattern recognition,Computer science,Segmentation,Spatial configuration,Geometric configuration,Image retrieval,Robustness (computer science),Inpainting,Pyramid,Artificial intelligence,3D reconstruction
Conference
Citations 
PageRank 
References 
1
0.35
16
Authors
2
Name
Order
Citations
PageRank
Harshit Agrawal1448.53
Anoop M. Namboodiri225526.36