Herbs Recognition Based on Android using OpenCV
Herbs are used in traditional medicine. There are so many herbs are spread across the world, it is difficult to memorize it all. This paper describes an android application to recognize herbs by their leaf characteristics (shape, veins, and keypoints). Shape and veins of leaves are recognized by Inv...
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| Veröffentlicht in: | International journal of image, graphics and signal processing graphics and signal processing, 2015-01, Vol.7 (2), p.1-7 |
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| creator | Agus Suryawibawa, I Wayan Gede Darma Putra, I Ketut Ayu Wirdiani, Ni Kadek |
| description | Herbs are used in traditional medicine. There are so many herbs are spread across the world, it is difficult to memorize it all. This paper describes an android application to recognize herbs by their leaf characteristics (shape, veins, and keypoints). Shape and veins of leaves are recognized by Invariant Moment Method as the feature extraction. City Block Distance used to calculate the distance between the features. Whereas for detection and keypoints extraction using Oriented FAST and Rotated BRIEF on OpenCV library. This keypoints distance calculation using Brute-Force Hamming. Matching is done by calculating the shortest distance between test image and reference image. If the result is less than or equal to threshold then image is match. Experiment result show this application can achieve 79% of success rate by using keypoints. This result is influenced by glossy leaf surface, so there is many reflected light that become noise. |
| doi_str_mv | 10.5815/ijigsp.2015.02.01 |
| format | Article |
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There are so many herbs are spread across the world, it is difficult to memorize it all. This paper describes an android application to recognize herbs by their leaf characteristics (shape, veins, and keypoints). Shape and veins of leaves are recognized by Invariant Moment Method as the feature extraction. City Block Distance used to calculate the distance between the features. Whereas for detection and keypoints extraction using Oriented FAST and Rotated BRIEF on OpenCV library. This keypoints distance calculation using Brute-Force Hamming. Matching is done by calculating the shortest distance between test image and reference image. If the result is less than or equal to threshold then image is match. Experiment result show this application can achieve 79% of success rate by using keypoints. 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There are so many herbs are spread across the world, it is difficult to memorize it all. This paper describes an android application to recognize herbs by their leaf characteristics (shape, veins, and keypoints). Shape and veins of leaves are recognized by Invariant Moment Method as the feature extraction. City Block Distance used to calculate the distance between the features. Whereas for detection and keypoints extraction using Oriented FAST and Rotated BRIEF on OpenCV library. This keypoints distance calculation using Brute-Force Hamming. Matching is done by calculating the shortest distance between test image and reference image. If the result is less than or equal to threshold then image is match. Experiment result show this application can achieve 79% of success rate by using keypoints. 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| title | Herbs Recognition Based on Android using OpenCV |
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