Classification of cotton leaf spot diseases using image processing edge detection techniques

Revathi, P.; Hemalatha, M.

doi:10.1109/incoset.2012.6513900

Cited by 124 publications

(31 citation statements)

References 5 publications

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“…The system proposed in [3] used the digital images that are obtained from the mobile . Then, image-processing techniques are applied on the acquired images to extract RGB Pixel counting features that are important for analysis.…”

Section: Image Processing Edge Detection Technique Used To Identifmentioning

confidence: 99%

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A Survey on Data Mining and Image Processing Techniques Used in Agriculture

Deshmukh¹

2018

IJRASET

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Data mining is used to extract the information from the large dataset and used to predict patterns and behavior of an application. Data mining plays a chief role in the fields of e-commerce, healthcare sector, and agricultural sector. Agriculture is the prime occupation in India. Crop productivity mainly depends on weather conditions. Data mining is used in agriculture to predict crop productivity, water management, crop disease management, pesticide recommendation by using different algorithms. Image processing techniques are also widely used to identify crop diseases using images of affected crops. The purpose of this survey is to study data mining and image processing techniques used in crop disease prediction and identification.

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Section: Image Processing Edge Detection Technique Used To Identifmentioning

confidence: 99%

“…This system consists of two phases to identify the disease. In [3] The image of a leaf is taken as an input image and is converted into a grey-scale image. Then color filter is applied and affected leaf spot color is used for RGB Pixel counting values and features are segmented.…”

Section: Image Processing Edge Detection Technique Used To Identifmentioning

confidence: 99%

A Survey on Data Mining and Image Processing Techniques Used in Agriculture

Deshmukh¹

2018

IJRASET

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“…The elements of the matrix indicate whether pairs of vertices are adjacent or not in the graph.In the special case of a finite simple graph, the adjacency matrix is a (0, 1)-matrix with zeros on its diagonal. If the graph is undirected, the adjacency matrix is symmetric [13], [17], [20]. The relationship between a graph and the eigenvalues and eigenvectors of its adjacency matrix is studied in spectral graph theory.…”

Section: B Adjacency Matrixmentioning

confidence: 99%

Harmonizing Real Time Data Using Maximum Weighted Graph Matching

2017

IJAERD

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“…F. Argenti, et al [2] proposed a fast algorithm for calculating parameters of co-occurrence matrix by supervised learning and maximum likelihood method for fast classification. Homogenize techniques like sobel and canny filter has been used to identify the edges by P.Revathi et al [3]. These extracted edge features have been used in classification to identify the disease spots.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The objective of this paper is to concentrate on the plant leaf disease detection based on the texture of the leaf. Leaf presents several advantages over flowers and fruits at all seasons worldwide [3], [4]. This paper is organized into the following sections.…”

Section: Introductionmentioning

confidence: 99%