Research Article
A Novel Feature Extraction Technique Using Binarization of Bit Planes for Content Based Image Classification
Table 5
Comparison of Precision, Recall, and Accuracy of different techniques.
| Techniques | Proposed | Feature extraction by binarization with multilevel mean threshold (existing) | Feature extraction by binarization using Bit Plane Slicing with mean threshold (existing) | Feature extraction by binarization of original + even image with mean threshold (existing) | Feature extraction by binarization with Bernsen’s local threshold method (existing) | Feature extraction by binarization with Sauvola’s local threshold method (existing) | Feature extraction by binarization with Niblack’s local threshold method (existing) | Feature extraction by binarization with Otsu’s global threshold method (existing) |
| Precision | 0.69 | 0.66 | 0.65 | 0.65 | 0.64 | 0.63 | 0.57 | 0.52 |
| Recall | 0.69 | 0.66 | 0.65 | 0.65 | 0.64 | 0.63 | 0.57 | 0.52 |
| Accuracy | 0.93 | 0.92 | 0.92 | 0.92 | 0.92 | 0.92 | 0.9 | 0.89 |
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