Thresholding Image Techniques for Plant Segmentation

Abstract

There are challenges in the image-based research to obtain information from the objects in the scene. Moreover, an image is a set of data points that can be processed as an object in similarity way. In addition, the research fields can be merged to generate a method for information extraction and pixel classification. A complete method is proposed to extract information from the data and generate a classification model capable to isolate those pixels that are plant from others are not. Some quantitative and qualitative results are shown to compare methods to extract information and create the best model. Classical and threshold-based state-of-art methods are grouped in the present work for reference and application in image segmentation, obtaining acceptable results in the plant isolation.