本课程主要由一系列讲义组成。同时也包含了相关的阅读材料，其中许多是由讲师本人编写的。课程议题是密切依照讲师的指定教材来组织的。

This course features a set of lecture notes. Related readings, many authored by the instructor, are included also. The topics follow closely the instructor's textbook.

机器视觉课程对于由一幅图像产生环境的符号性描述的过程进行了透彻的介绍。讲稿叙述了图像格式的物理特征、运动视觉以及由阴影恢复形状。二值化图像的处理和滤波技术作为图像预处理步骤来介绍。进一步的课题涵盖了照相测量学、物体表现平面图、模拟超大规模集成电路（VLSI）和计算视觉技术。此外，机器视觉在机器人和智能设备交互方面的应用也在本课程的讨论之列。

Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed.