@inproceedings{16891d7f532946f394140619cbbb0f8f,
title = "Active Contour Texture Segmentation in Modulus Wavelet Feature Spaces",
abstract = "In this paper we discuss a model that is able to segment textures using active contours. Our technique is based on active contour techniques using. curve evolution. We build our model on properties of human vision, in that we segment the textures in a certain feature space. We will show the advantages of using modulus feature spaces. Wavelet coefficients are shown to exhibit local features both in space and frequency domains. We will implement our model in modulus wavelet subbands.",
keywords = "Image Processing, Pattern Recognition and Data Mining, Computer Vision",
author = "Ashoka Jayawardena and Kwan, \{Paul H\}",
year = "2013",
doi = "10.1007/978-1-4614-3535-8\_45",
language = "English",
isbn = "9781461435341",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer",
number = "152",
pages = "537--544",
editor = "Khaled Elleithy and Tarek Sobh",
booktitle = "Innovations and Advances in Computer, Information, Systems Sciences, and Engineering",
edition = "1",
note = "CISSE 2011: International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering ; Conference date: 03-12-2011 Through 12-12-2011",
}