Data mining and Knowledge Discovery is a promising area of research that has been drawing several researchers to mine significant portions of information from the image dataset. Citrus fruit image examination and Knowledge Discovery from an Image is also delightful the front position in both Data Mining and Image processing area. Citrus fruit image data classification process is capable as a valuable for discovering the fruit disease categorization and associations with disease data. Citrus fruit data feature vector classification is a major task of data mining. In this paper to develop a novel Image Data mining Feature Vector pre-processing using Enhanced Gabor Wavelet (EGW) with Feature Vector Correlogram (FVC) algorithm to converting the citrus fruit diseases as training vectors. To identify the data mining training vector prediction in citrus fruit, the EGW-FVC algorithm has to be described. The proposed work of a citrus fruit data vector prediction process presents three tasks namely, i) Image pre-processing:; ii) Citrus fruit features extraction: iii) Graph based Recuro Match and (iv) Image Data Feature Vector pre-processing is significant process to converting a training dataset feature of an image.
Volume 11 | 04-Special Issue
Pages: 2503-2509