A machine-vision-system-guided precision sprayer was developed and tested. The long-term objectives of this project were to develop new technologies to estimate weed density and size in real time, realize site-specific weed control, and effectively reduce herbicide application amounts for corn and soybean fields. This research integrated a real-time machine-vision sensing system with an automatic herbicide sprayer to create an intelligent sensing and spraying system. Multiple video images were used to cover the target area. To increase the accuracy, each individual spray nozzle was controlled separately. Instead of trying to identify each individual plant in the field, weed infestation zones (0.254 m × 0.34 m) were detected. The integrated system was tested to evaluate the effectiveness and performance under varying field conditions. With the current system design, and using 0.5% weed coverage as the control zone threshold, herbicide savings of 48% could be realized.