@inproceedings{941eaabc5ba64a1d8168d87ff5dc5674,
title = "Sketch-based image retrieval using contour segments",
abstract = "The paper presents a sketch-based image retrieval algorithm. One of the main challenges in sketch-based image retrieval (SBIR) is to measure the similarity between a sketch and an image in contour with high precision. To tackle this problem, we divided the contour of image into two types: the first is global contour, suggesting that we can use it to reduce the similarity between the images with complex background. The second, called salient contour, is helpful to retrieve images with objects similar to the query. Besides, we propose a new descriptor, namely angular radial orientation partitioning (AROP) feature, which makes full use of the gradient orientation information to decrease the gap between sketch and image. Using the two contours as candidate contours for feature extraction could increase the retrieval rate dramatically. Finally an application of retrieval system based on this algorithm is established. The experiment on 0.42 million image dataset shows excellent retrieval performance of the proposed method and comparisons with other algorithms are also given.",
keywords = "Detectors, Feature extraction, Histograms, Image edge detection, Image retrieval, Indexes, Shape",
author = "Yuting Zhang and Xueming Qian and Xianglong Tan",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015 ; Conference date: 19-10-2015 Through 21-10-2015",
year = "2015",
month = nov,
day = "30",
doi = "10.1109/MMSP.2015.7340836",
language = "英语",
series = "2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015",
}