Discrete Cosine Transformation and Height Functions Based Shape Representation and Classification
| Autor: | B. H. Shekar, Bharathi Pilar |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Combined classifier
Height Functions Computer science business.industry Shape classification Pattern recognition Shape representation Discrete cosine transformation Dynamic programming Euclidean distance Nonlinear system Discrete cosine transform General Earth and Planetary Sciences Decision fusion Artificial intelligence Discrete Cosine Transformation business Classifier (UML) Transformation geometry General Environmental Science |
| Zdroj: | Procedia Computer Science. 58:714-722 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2015.08.092 |
| Popis: | In this paper, we propose a combined classifier model based on two dimensional discrete cosine transform (2D-DCT) and Height Functions (HF) for accurate shape representation and classification. The DCT is capable of capturing the region information and Height Functions are insensitive to geometric transformations and nonlinear deformations. The Euclidean distance metric in case of DCT and Dynamic Programming (DP) in case of HF were respectively employed to obtain similarity values and hence fused to classify given query shape based on minimum similarity value. The experiments are conducted on publicly available shape datasets namely MPEG-7, Kimia-99, Kimia-216, Myth and Tools-2D and the results are presented by means of bull's eye score and precision-recall metric. The comparative study is also provided with the well known approaches to exhibit the retrieval accu- racy of the proposed approach. The experimental results demonstrate that the proposed approach yields significant improvement over some of the well known algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|