Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib
Planting a plant is one of a method to control a current globe temperature. Plant features recognition has been performed by several researchers previously. Wu et al. [1] has performed the leaf recognition by using Probabilistic Neural Network (PNN) in order to classify the plants. As a result Wu et...
| Main Authors: | , , |
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| Format: | Research Reports |
| Language: | English |
| Published: |
Institute of Research Management & Innovation (IRMI)
2013
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/20147/ |
| _version_ | 1848804946657411072 |
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| author | Ab Jabal, Mohamad Faizal Hamid, Suhardi Shuib, Salehuddin |
| author_facet | Ab Jabal, Mohamad Faizal Hamid, Suhardi Shuib, Salehuddin |
| author_sort | Ab Jabal, Mohamad Faizal |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Planting a plant is one of a method to control a current globe temperature. Plant features recognition has been performed by several researchers previously. Wu et al. [1] has performed the leaf recognition by using Probabilistic Neural Network (PNN) in order to classify the plants. As a result Wu et al. [1] was successful developed an efficient algorithm for the plant classification. 32 kinds of plants have been classified by using the algorithm. The basic leaf features considered by the algorithm had been defined by Wu et al. [1] involved diameter of the leaf, physiological length, physiological width, leaf area and leaf perimeter. Moreover, from the basic leaf features, Wu et al. [1] had defined several digital morphological features which are involved smooth factor, aspect ratio, form factor, rectangularity, narrow factor, vein features and perimeter ratio of diameter, physiological length and width. Final result produced by the algorithm is 92.312% of average accuracy and the classification for the leaf was based on the leaf-shape information. |
| first_indexed | 2025-11-14T22:03:13Z |
| format | Research Reports |
| id | uitm-20147 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T22:03:13Z |
| publishDate | 2013 |
| publisher | Institute of Research Management & Innovation (IRMI) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-201472019-02-13T04:37:17Z https://ir.uitm.edu.my/id/eprint/20147/ Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib Ab Jabal, Mohamad Faizal Hamid, Suhardi Shuib, Salehuddin Plant anatomy Plant physiology Planting a plant is one of a method to control a current globe temperature. Plant features recognition has been performed by several researchers previously. Wu et al. [1] has performed the leaf recognition by using Probabilistic Neural Network (PNN) in order to classify the plants. As a result Wu et al. [1] was successful developed an efficient algorithm for the plant classification. 32 kinds of plants have been classified by using the algorithm. The basic leaf features considered by the algorithm had been defined by Wu et al. [1] involved diameter of the leaf, physiological length, physiological width, leaf area and leaf perimeter. Moreover, from the basic leaf features, Wu et al. [1] had defined several digital morphological features which are involved smooth factor, aspect ratio, form factor, rectangularity, narrow factor, vein features and perimeter ratio of diameter, physiological length and width. Final result produced by the algorithm is 92.312% of average accuracy and the classification for the leaf was based on the leaf-shape information. Institute of Research Management & Innovation (IRMI) 2013-05 Research Reports NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/20147/1/LP_MOHAMAD%20FAIZAL%20AB%20JABAL%20IRMI%20K%2013_5.pdf Ab Jabal, Mohamad Faizal and Hamid, Suhardi and Shuib, Salehuddin (2013) Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib. (2013) [Research Reports] (Unpublished) |
| spellingShingle | Plant anatomy Plant physiology Ab Jabal, Mohamad Faizal Hamid, Suhardi Shuib, Salehuddin Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib |
| title | Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib |
| title_full | Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib |
| title_fullStr | Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib |
| title_full_unstemmed | Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib |
| title_short | Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib |
| title_sort | hevea leaf features extraction and recognition algorithm for hevea clones classification using image / mohamad faizal ab jabal, suhardi hamid, salehuddin shuib |
| topic | Plant anatomy Plant physiology |
| url | https://ir.uitm.edu.my/id/eprint/20147/ |