204 Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 9 DOI: 10.4018/978-1-7998-1839-7.ch009 ABSTRACT Each crop has their own weed problems. Therefore, to understand each problem, agronomists and weed scientists must be able to determine the weed abundance with the most precise method. There are several techniques to scouting, including visual counting for density or estimations for coverage of weeds. However, this technique depends by the evaluator subjectivity, performance, and training, causing errors and bias when estimating weeds abundance. This chapter introduces a methodology to process multispectral images, based on histograms of oriented gradients and support vector machines to detect weeds in lettuce crops. The method was validated by experts on weed science, and the statisti- cal diferences were calculated. There were no signifcant diferences between expert analysis and the proposed method. Therefore, this method ofers a way to analyze large areas of crops in less time and with greater precision. Weed Estimation on Lettuce Crops Using Histograms of Oriented Gradients and Multispectral Images Andres Esteban Puerto Lara https://orcid.org/0000-0002-3818-5667 Fundacion Universitaria Panamericana, Colombia Cesar Pedraza Universidad Nacional de Colombia, Colombia David A. Jamaica-Tenjo Universidad Nacional de Colombia, Colombia