Abstract:
High dimensionality and multi-feature combinations can have negative effect on
visual concept classification. In our research, we formulated a new compacted form which
is Compacted Dither Pattern Code (CDPC) as a chromatic syntactic feature for visual
feature extraction. The effectiveness of CDPC with Bhattacharyya classifier for irregular
shapes based visual concepts depiction is reported in this paper. The proposed technique
can reduce feature space and computational complexity while maintaining visual data
mining and retrieval accuracy in high standard. Our system was empowered with
Bhattacharyya classifier which has improved efficiency by considering one numeric value
which is the Bhattacharyya coefficient. Experiments were conducted on various
combinations and compared with different visual descriptors and classifiers. The first
experiment illustrates the comparison of the CDPC based results with well known feature
space reduction classes. The second and third experiments demonstrate the effectiveness of
our approach with multiple perspectives of performance measures including various
concepts.
