Fundamentals of digital image processing
Fundamentals of digital image processing
The revised Fundamental Theorem of Moment Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
Run-Based Algorithms for Binary Image Analysis and Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Picture Processing
A pipeline architecture for computing the Euler number of a binary image
Journal of Systems Architecture: the EUROMICRO Journal
Local Properties of Binary Images in Two Dimensions
IEEE Transactions on Computers
Euler vector for search and retrieval of gray-tone images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Archival image indexing with connectivity features using randomized masks
Applied Soft Computing
| Hi-index | 0.14 |
A new combinatorial feature called Stacked Euler Vector (SERVE) is introduced to characterize a gray-tone image. SERVE comprises a four-tuple, where each element is an integer representing the Euler number of the partial binary image formed by certain pixel overlap relations among the four most significant bit planes of the gray-tone image. Computation of SERVE is simple, fast, and does not involve any floating point operation. SERVE can be used to augment other features to improve the performance of image retrieval significantly. Experimental results on the COIL database are reported to demonstrate its performance.