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Title |
Automated Flower Species Detection and Recognition from Digital Images |
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Author |
Aalaa Albadarneh and Ashraf Ahmad |
| Citation |
Vol. 17 No. 4 pp. 144-151 |
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Abstract |
Automated flower species recognition has been studied for many years. Differences between these studies come from features which were extracted from the flower image, and the recognition algorithm that was used to recognize the flower species. A new automated system was adapted to detect the flower region from the image and recognize its species. Features based on color, texture, and shape were extracted from the interest part only, so the recognition accuracy is increased. New Dataset has been built which contains flowers from Jordan. The result showed a high recognition accuracy of our new dataset. In addition, our proposed system outperforms several methods on Oxfoed17 Dataset. |
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Keywords |
Automated, Detection, Recognition, Digital Image processing. |
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