Plant Diseases Detection Based on Color Features and Kapur’s method
نویسنده
چکیده
Plant diseases have become an important issue because they cause important reduction in each quality and amount of agricultural products. Automatic detection of plant diseases is an important analysis topic because it could significantly help in observation giant fields, and enable automatic detection the symptoms of diseases as soon as they appear on the plant leaves. In this paper an algorithm for plant disease detection using different color models is proposed and tested. Plant leaf images were first transformed into RGB, YCbCr, HSI or CIELAB color model. Noise in transformed image was reduced by applying median filter. At the end, disease spots were detected by using Kapur’s thresholding method. Based on the experimental results, HSI color model is the most suitable for automatic plant disease detection, while RGB is practically unusable. Key–Words: CIELAB, HSI, YCbCr, plant leaf disease detection, image thresholding, Kapur’s method
منابع مشابه
The Combinational Use Of Knowledge-Based Methods and Morphological Image Processing in Color Image Face Detection
The human facial recognition is the base for all facial processing systems. In this work a basicmethod is presented for the reduction of detection time in fixed image with different color levels.The proposed method is the simplest approach in face spatial localization, since it doesn’trequire the dynamics of images and information of the color of skin in image background. Inaddition, to do face...
متن کاملA Saliency Detection Model via Fusing Extracted Low-level and High-level Features from an Image
Saliency regions attract more human’s attention than other regions in an image. Low- level and high-level features are utilized in saliency region detection. Low-level features contain primitive information such as color or texture while high-level features usually consider visual systems. Recently, some salient region detection methods have been proposed based on only low-level features or hig...
متن کاملAn Image Processing and Neural Network Based Approach for Detection and Classification of Plant Leaf Diseases
In the present paper we propose and evaluate a framework for detection and classification of plant leaf/stem diseases using image processing and neural network technique. The images of plant leaves affected by four types of diseases namely early blight, late blight, powdery-mildew and septoria has been considered for study and evaluation of feasibility of the proposed method. The color transfor...
متن کاملIntegration of Color Features and Artificial Neural Networks for In-field Recognition of Saffron Flower
ABSTRACT-Manual harvesting of saffron as a laborious and exhausting job; it not only raises production costs, but also reduces the quality due to contaminations. Saffron quality could be enhanced if automated harvesting is substituted. As the main step towards designing a saffron harvester robot, an appropriate algorithm was developed in this study based on image processing techniques to recogn...
متن کاملDetermining Effective Features for Face Detection Using a Hybrid Feature Approach
Detecting faces in cluttered backgrounds and real world has remained as an unsolved problem yet. In this paper, by using composition of some kind of independent features and one of the most common appearance based approaches, and multilayered perceptron (MLP) neural networks, not only some questions have been answered, but also the designed system achieved better performance rather than the pre...
متن کامل