Name
Abstract | ||
|---|---|---|
We present in this paper a new approach for hand gesture analysis that allows
digit recognition. The analysis is based on extracting a set of features from a
hand image and then combining them by using an induction graph. The most
important features we extract from each image are the fingers locations, their
heights and the distance between each pair of fingers. Our approach consists of
three steps: (i) Hand detection and localization, (ii) fingers extraction and
(iii) features identification and combination to digit recognition. Each input
image is assumed to contain only one person, thus we apply a fuzzy classifier
to identify the skin pixels. In the finger extraction step, we attempt to
remove all the hand components except the fingers, this process is based on the
hand anatomy properties. The final step consists on representing histogram of
the detected fingers in order to extract features that will be used for digit
recognition. The approach is invariant to scale, rotation and translation of
the hand. Some experiments have been undertaken to show the effectiveness of
the proposed approach. |
Year | Venue | Keywords |
|---|---|---|
2009 | Clinical Orthopaedics and Related Research | pattern recognition |
Field | DocType | Volume |
Histogram,Computer vision,Graph,Pattern recognition,Computer science,Gesture analysis,Pixel,Invariant (mathematics),Artificial intelligence,Digit recognition,Fuzzy classifier | Journal | abs/0906.5 |
ISSN | Citations | PageRank |
IJCSIS June 2009 Issue, Vol. 2, No. 1 | 3 | 0.42 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| ahmed ben jmaa | 1 | 3 | 0.76 |
| Walid Mahdi | 2 | 116 | 25.49 |
| Yousra Ben Jemaa | 3 | 48 | 9.08 |
| Abdelmajid Ben Hamadou | 4 | 353 | 56.16 |