Authors:
Yan Sun
and
Xiaomu Niu
Affiliation:
Queen Mary University of London, United Kingdom
Keyword(s):
Scale-Invariant Feature Transform, Perception Hash, Support Vector Machines, Bag of Features, Perceptual Hash Distance.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Digital Photography
;
Entertainment Imaging Applications
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Generation Pipeline: Algorithms and Techniques
;
Mobile Imaging
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
Abstract:
In recent years, several art museums have developed smartphone applications as the e-guide in museums.
However few of them provide the function of instant retrieval and identification for a painting snapshot taken
by mobile. Therefore in this work we design and implement an oil portrait classification application on
smartphone. The accuracy of recognition suffers greatly by aberration, blur, geometric deformation and
shrinking due to the unprofessional quality of snapshots. Low-megapixel phone camera is another factor
downgrading the classification performance. Carefully studying the nature of such photos, we adopts the SIPH
algorithm (Scale-invariant feature transform based Image Perceptual Hashing)) to extract image features and
generate image information digests. Instead of popular conventional Hamming method, we applied an
effective method to calculate the perceptual distance. Testing results show that the proposed method conducts
satisfying performance on robustness and discrimi
nability in portrait snapshot identification and feature
indexing.
(More)