Abstract
In this paper, we propose a novel method for plant leaves recognition by incorporating an unsupervised convolutional auto-encoder (CAE) and Siamese neural network in a unified framework by considering Siamese as an alternative to the conventional loss of CAE. Rather than the conventional exploitation of CAE and Siamese, in our case we have proposed to extend CAE for a novel supervised scenario by considering it as one-class learning classifier. For each class, CAE is trained to reconstruct its positive and negative examples and Siamese is trained to distinguish the similarity and the dissimilarity of the obtained examples. On the contrary and asymmetric to the related hierarchical classification schemes which require pre-knowledge on the dataset being recognized, we propose a hierarchical classification scheme that doesn’t require such a pre-knowledge and can be employed by non-experts automatically. We cluster the dataset to assemble similar classes together. A test image is first assigned to the nearest cluster, then matched to one class from the classes that fall under the determined cluster using our novel one-class learning classifier. The proposed method has been evaluated on the ImageCLEF2012 dataset. Experimental results have proved the superiority of our method compared to several state-of-the art methods.
Highlights
Plants have a significant impact on human life and development; without them, there will be no existence of the earth’s ecology [1]
We propose a hierarchical classification scheme that doesn’t require pre-knowledge, and which can be used by non-experts
The results show that Zernike Moments have a prospect as features in leaf identification systems once they are combined with other features
Summary
Plants have a significant impact on human life and development; without them, there will be no existence of the earth’s ecology [1]. Plants play a decisive role in providing oxygen, clean air, food, etc. They contribute to several tasks of scientists from different domains such as agriculture, medicine, and environmental fields. With the huge number of plants that exist on the earth classification through experts and botanists is subjective and requires much effort from experts. This process is too expensive in terms of time and effort
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