A texture-based approach for content based image retrieval system for plant leaves images

Ahmed Naser Hussein, S. Mashohor, M. Saripan
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引用次数: 21

Abstract

Image identification of plant leaves based on human vision is difficult task as well as plant identification based on keywords retrieval. It requires the domain knowledge in the botanist field. This work proposes the image texture analysis using Discrete Wavelet Transformation (DWT) and combined with an entropy measurement to identify a query image to one of seven classes that consists of 280 plant leaves images. The experimental results show that the proposed method yields higher correctness retrieval accuracy rate which reaches up to 92% compared to the Gray Level Co-occurrence Matrix (GLCM) that gives 49.28%.
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一种基于纹理的植物叶片图像检索系统
基于人类视觉的植物叶片图像识别和基于关键词检索的植物识别都是一个难题。这需要植物学家领域的专业知识。本文提出了使用离散小波变换(DWT)和熵测量相结合的图像纹理分析方法,将查询图像识别为由280个植物叶片图像组成的七个类别之一。实验结果表明,与灰度共生矩阵(GLCM)的49.28%的检索准确率相比,该方法的检索准确率高达92%。
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