Plant identification through images: Using feature extraction of key points on leaf contours¹

Abstract

• Premise of the study: Because plant identification demands extensive knowledge and complex terminologies, even professional botanists require significant time in the field for mastery of the subject. As plant leaves are normally regarded as possessing useful characteristics for species identification, leaf recognition through images can be considered an important research issue for plant recognition.• Methods: This study proposes a feature extraction method for leaf contours, which describes the lines between the centroid and each contour point on an image. A length histogram is created to represent the distribution of distances in the leaf contour. Thereafter, a classifier is applied from a statistical model to calculate the matching score of the template and query leaf.• Results: The experimental results show that the top value achieves 92.7% and the first two values can achieve 97.3%. In the scale invariance test, those 45 correlation coefficients fall between the minimal value of 0.98611 and the maximal value of 0.99992. Like the scale invariance test, the rotation invariance test performed 45 comparison sets. The correlation coefficients range between 0.98071 and 0.99988.• Discussion: This study shows that the extracted features from leaf images are invariant to scale and rotation because those features are close to positive correlation in terms of coefficient correlation. Moreover, the experimental results indicated that the proposed method outperforms two other methods, Zernike moments and curvature scale space.

Fully-automatic natural plant recognition system using deep neural network for dynamic outdoor environments

“…A series of measurements, like area, perimeter, maximum length, maximum width, compactness and elongation [18], have been carried out, but this proposed method cannot be utilized in all conditions and situations. In [19], leaf contour is performed by using a feature extraction method and plant identification has been carried out through the images. The method used can be applied and utilized for artificial images.…”

TRIST: Tree Recognition Intelligent System

“…So, the performance of the systems employing this approach depends heavily on the underlying predefined features. In the plant identification literature, there are some common leaf features used for classification, such as circularity, eccentricity, roundness, aspect ratio [4]. However, the feature engineering process is quite complex and tedious, always needing extensive revision when changing the dataset.…”

“…Plant recognition implies the use of leaves, flowers, bark or a combination between them, in order to identify the corresponding species. As a result, a lot of research papers were published on this topic, such as [1,2,4,6,7,10,12,13,14,16,17,18]. Plant identification is also quite a difficult task for humans to accomplish because it requires domainspecific expertise, as well as experience.…”

Plant Leaf Recognition System Using Kernel Ensemble Approach

“…The prediction is done by MLP architecture. Leaf contour based features is described in [6] for PLR. A histogram is formed using distances from the center of the leaf to the contour.…”