Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area

Abstract

In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.

Plant phenotyping relevance

植物の葉面積・花弁面積・病斑面積を画像から抽出する手法を開発し、人工ラベリングと比較検証しており、表現型取得手法が研究の中心です。

Code and data availability

The article describes collection of 501 butterfly petal images and Bauhinia/phyllotaxus lesion images and an OpenCV-based analysis pipeline, but contains no data availability statement, no public dataset deposit, and no code availability or repository URL. No paper-specific public asset is identified.

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