Feature Extraction Of Leaf Area Based On Digital Image Processing

With the continuous development of the Internet, the network has become more and more important in people's lives. Leaf is an important organ of plants. Plants have different features at different growth phases. Shape, color and thickness are the main features of plant leaf. Leaf length, width and area are important parts of plant morphological features. Their changes are significant to plant research and production guidance for agriculture and forestry. Most traditional methods of leaf area measurements are conducted by hand with low efficiency. Leaf area measurement based on image processing technology, however, may be used as an effective tool to extract leaf features automatically. Image processing technology is applied to analyze leaf area features in this paper. Binary images of Populus tomentosa Carr leaves at different growing stages are obtained through procedures of pre-processing, binarization and morphological operation. Images of leaves with distortions are corrected through the application of Hough transform and space transformation. As a result, regression equations are built based on data of lengths, breadth and areas of sample leaves acquired. Finally, I created a animation used Flash software based on the data obtained.This paper describes an experiment in which leaf features (basically data of leaf areas at different growing stages) of Populus tomentosa Carr are extracted based on digital image processing technology. Also regression equations are built which indicates the relationship between leaf length, width, areas and its stages of growth. The experiments of this paper provided foundation for research of visualization of plant, crop production, and the performance of the network animation art.