Ficus is one of the largest genera in plant kingdom reaching to about 1000 species worldwide. While taxonomic keys are available for identifying most species of Ficus, it is very difficult and time consuming for interpretation by a nonprofessional thus requires highly trained taxonomists. The purpose of the current study is to develop an efficient baseline automated system, using image processing with pattern recognition approach, to identify three species of Ficus, which have similar leaf morphology. Leaf images from three different Ficus species namely F. benjamina, F. pellucidopunctata and F. sumatrana were selected. A total of 54 leaf image samples were used in this study. Three main steps that are image pre-processing, feature extraction and recognition were carried out to develop the proposed system. Artificial neural network (ANN) and support vector machine (SVM) were the implemented recognition models. Evaluation results showed the ability of the proposed system to recognize leaf images with an accuracy of 83.3%. However, the ANN model performed slightly better using the AUC evaluation criteria. The system developed in the current study is able to classify the selected Ficus species with acceptable accuracy.

榕属植物界中最大的属之一，全世界约有1000种。虽然分类键可用于识别大多数榕属植物，但非专业人员的解释非常困难且耗时，因此需要训练有素的分类学家。本研究的目的是开发一种有效的基线自动化系统，该系统使用具有模式识别方法的图像处理来识别三种具有相似叶片形态的榕属植物。从三个不同的图像叶榕树种即垂叶榕，F. pellucidopunctata和F.苏门答腊被选中。这项研究总共使用了54个叶片图像样本。进行了三个主要步骤，即图像预处理，特征提取和识别，以开发所提出的系统。人工神经网络（ANN）和支持向量机（SVM）是实现的识别模型。评估结果表明，提出的系统能够以83.3％的精度识别叶子图像。但是，使用AUC评估标准，ANN模型的性能稍好。当前研究中开发的系统能够以可接受的准确度对选定的榕属物种进行分类。