The Comprehensive Review on Early Detection of Macro Nutrients Deficiency Based on Image Processing Technique Lia Kamelia , Titik Khawa Abdul Rahman, Reni Haerani
UIN Sunan Gunung Djati Bandung
Asia e-University , Selangor Malaysia
Politeknik PGRI Banten
Abstract
Images are the significant source of data and information in the agricultural technologies. The use of image processing techniques had important implication for the analysis of smart farm. The analytical system using digital image processing would classify the nutrient deficiency symptoms much prior than human could identify. This will enable the farmers to adopt appropriate corrective action in time. The paper discusses various methods used in the detection of nutrient deficiencies in plants based on visual images. The image processing techniques has several stages to get the best results in nutrient deficiency detection, namely image acquisition, image enhancement, image segmentation, and feature extraction. Through analysis and discussion, the paper proposed new technique in every phase of image processing for the detection of nutrient deficiency as the basic of the implementation in future research.in the future the image processing will be more broadly used to resolve the nutrient deficiency detection problems, and will expand the crops quality and quantity with universal and robust performance of farming automation systems, consequently the research will support the growth of agricultural automation equipment and systems in a more smart approaches.
