Image Features Evaluation Using New Algorithm Proposed For Reducing Image Feature Number & Size Stored In Database | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 29, Issue 6, April 2011, Pages 1176-1194 PDF (562.71 K) | ||
| DOI: 10.30684/ etj.29.6.12 | ||
| Author | ||
| Shahlaa T. Abdulwahab | ||
| Abstract | ||
| This study proposes technique that capable of reducing image features size and number stored in the database. The proposed technique depends on the image content of numerical values for the three basic colors (red, green and blue) and then stores it in the database and to be used for image retrieval. This technique has been developed based on recent image retrieval procedures that include Color Descriptor Matrix, YCbCr Color Space and Discrete Cosine Transform. Those procedures have been applied sequentially on the image and finally Kekre’s Transform has been applied in the last stage of this technique to evaluate image features and reduce its stored size in the database. The validity and accuracy of the proposed technique have been evaluated through experiments by applying Kekre’s Transform on Color Descriptor Matrix instead of using Kekre’s Transform directly on the image in order to reduce its feature stored size. Another experiments have been tested and evaluated that include the application of YCbCr Color Space on the Color Descriptor Matrix and finally Kekre’s Transform to be executed and explore the image features size and compare it with the previous stage. The effect of applying the Discrete Cosine Transform on the YCbCr Color Space and finally the Kekre’s Transform on the image features size has been studied and compared with the previous step. It is concluded that the best reduction in image features size stored in the database can be obtained only when Kekre’s Transform applied in the last step of the proposed technique with unchanged threshold based image retrieval ratios. Parametric study has been conducted to investigate the effect of applying the new algorithm on both isolated and mixed image groups. Good precision ratios of 82% and 65% have been obtained for the isolated and mixed image groups respectively. | ||
| Keywords | ||
| image retrieval; Kekre; YCbCr Color Space; Discrete Cosine Transform | ||
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