基于人工神经网络分类的植物叶片识别

2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) Pub Date : 2022-12-26 DOI:10.1109/ICERECT56837.2022.10060430

P. G K, Virupakshaiah H K, B. P. T., A. Karegowda, Tejaswini K M, K. K.

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引用次数: 0

摘要

提出了最先进的寻找象形四种叶(花、果、医、树)识别的方法。采用边缘检测的局部特征边界来表示树叶，然后应用凸包算法。在第二阶段，利用第一阶段识别的特征，应用人工神经网络对系统进行模拟。训练数据和测试数据的平均识别率分别为96.75%和94%。

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Plant foliage Recognition based on Classification using Artificial Neural Network

The state-of-the-art method to find the pictographic four types of foliage (flower, fruit, medical and tree) identification is proposed. Foliage is represented by a boundary of local feature using edge detection, followed by applying convex hull algorithm. In the second phase, ANN has been applied for simulating the system using the features identified in first phase. The proposed work resulted in an average identification rate of 96.75% and 94% with training and test data.

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来源期刊

2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)

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