ALOHA: An efficient binary descriptor based on Haar features

This paper introduces ALOHA (Aggregated LOcal HAar), a compact and efficient binary descriptor based on a small number of intensity difference tests to represent an image patch as a binary string. ALOHA uses a set of features, reminiscent of Haar basis functions, to group pixels within a patch cente...

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Bibliographic Details
Published in2012 19th IEEE International Conference on Image Processing pp. 2345 - 2348
Main Authors Saha, S., Demoulin, V.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2012
Subjects
Accuracy
binary descriptor
Computational complexity
Detectors
Haar features
Hamming distance
Image coding
Image recognition
local feature
Robustness
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Summary:This paper introduces ALOHA (Aggregated LOcal HAar), a compact and efficient binary descriptor based on a small number of intensity difference tests to represent an image patch as a binary string. ALOHA uses a set of features, reminiscent of Haar basis functions, to group pixels within a patch centered on a keypoint. It has been compared with two version of BRIEF, the current best in class short binary descriptors. Even though the matching time for both descriptors is identical, ALOHA is faster to compute, and ensures better matching accuracy and discrimination capacity.
ISBN:1467325341
9781467325349
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2012.6467367