Disease Detection in Spinach Leaves using Image Processing and Machine Learning

Abstract: The 45% primary sector of our nation depends greatly on the growth and development of vegetables and edible leaves especially during hot summer where that won’t be a suitable period for other major staple productions. The spinach leaves paves a great role in that manner. The unhealthy leaves can cause decreased production that thus can lead indirectly to the declined development of the nation. Thus, we need to find a solution for the cause. Considering a general solution, it requisite enormous amount of work, mystery in the leaf diseases and it also needs huge amount of time. Thus, Image processing techniques along with the Machine learning algorithms can make process easier and successful. Spinach leaf disease detection and identification includes the process like acquisition, pre-processing, segmentation, feature extraction, classification and SMTP functioning. This paper discusses techniques for image pre-processing, image segmentation algorithm used for automatic recognition and research on various plant leaf disease classification algorithms that may be used for leaves disease classification.

Keywords: Image processing; Segmentation; Correlation; K-mean cluster Algorithm.