Image-based plant stornata phenotyping
Laga, H., Shahinnia, F. and Fleury, D. (2014) Image-based plant stornata phenotyping. In: 13th International Conference on Control, Automation, Robotics and Vision (ICARCV) 2014, 10 - 12 December 2014, Marina Bay Sands, Singapore
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We propose in this paper a fully automatic approach for image-based plant stomata phenotyping. Given a microscopic image of a plant leaf surface, our goal is to automatically detect stomata cells and measure their morphological and structural features, such as stomata opening length and width, and size of the guard cells. The main challenge in developing such tool is the lack of contrast between the stomata cell region and its surrounding background. Our approach uses template matching to detect individual stomata cells and local analysis to measure stomata features within the detected stomata regions. It is fully automatic and computationally efficient. Thus, it will enable plant biologists to perform large scale analysis of stomata morphology, which in turn will help in developing understanding and controlling plant's response to various environmental stresses (e.g. drought and soil salinity).
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