Journal of Computer Science


Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib and Illiasaak Ahmad

DOI : 10.3844/jcssp.2013.1295.1304

Journal of Computer Science

Volume 9, Issue 10

Pages 1295-1304


Plant classification based on leaf identification is becoming a popular trend. Each leaf carries substantial information that can be used to identify and classify the origin or the type of plant. In medical perspective, images have been used by doctors to diagnose diseases and this method has been proven reliable for years. Using the same method as doctors, researchers try to simulate the same principle to recognise a plant using high quality leaf images and complex mathematical formulae for computers to decide the origin and type of plants. The experiments have yielded many success stories in the lab, but some approaches have failed miserably when tested in the real world. This happens because researchers may have ignored the facts that the real world sampling may not have the luxury and complacency as what they may have in the lab. What this study intends to deliver is the ideal case approach in plant classification and recognition that not only applicable in the real world, but also acceptable in the lab. The consequence from this study is to introducing more external factors for consideration when experimenting real world sampling for leaf recognition and classification does this.


© 2013 Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib and Illiasaak Ahmad. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.