Leaf Image Processing and Detection: Computer-based Aid for Plant Identification and Classification

Author's: Fiza Fida, Muhammad Ramzan Talib, Nauman Ali Khan, Muhammad Aqeel, Naeem Iqbal, Faiza Fida, Muhammad Zahid, Muhammad Arshad, Ali Noman
Authors' Affiliations
Article Type: Research Article     Published: Aug. 20, 2018 Pages: 132-139
DOI:        Views 1837       Downloads 0


Identification/recognition of leaf is the first choice for plant taxonomist as well as common men. Plant taxonomists use different criteria for selection and identification of any plant species. Over the years, scientists used different processing tools to recognize plant images for identification of plant characteristics. To unveil the differences in the leaf Morphology with respect to plant identification, Faisalabad district was visited and surveyed for distribution of plant species. We developed leaf recognition software to facilitate the novice to understand the taxonomy of plant by just highlighting the attributes of plant leaves. A pipe and filter software architecture were applied and executed to implement this software. After precise confirmation, data regarding leaf attributes was extracted and used as a base for this software. We evaluated our system in a very extensive manner and also checked the impact. 153 leaf images prototype data was evaluated both with as well as without considering leaf self-intersection. The objective was to know whether an unknown leaf falls in one of the families and represent which plant group. Our system detected the most similar plant to the input options and can facilitate the users to reach a final conclusion. The final results pointed out a capable presentation of this software and its advantage over the classical method.


Classification, Image, Plants, Processing.


Fida, F., Talib, M.R., Khan, N.A., Aqeel, M., Iqbal, M., Fida, F., Zahid, M., Arshad, M., Noman, A., 2018. Leaf Image Processing and Detection: Computer-based Aid for Plant Identification and Classification. PSM Biol. Res., 3(3): 132-139.