Segmentation Based Image Mining Algorithms for Productivity of E-Cultivation

Abstract

Image Mining techniques are suggested for agriculture for crop quality-evaluation and defect identification. A review of some of the important segmentation based algorithms and recent trends in image processing techniques which are applicable to crop quality evaluation and defect identification is presented. Image segmentation techniques are used for the detection of diseases. This demonstrates the use of the  Agriculture information system, E-Cultivation process for increasing the productivity. Sample Results of some of the image segmentation algorithms used for crop disease identification and productivity measurement in E-Cultivation which are obtained using math lab are presented.