In this course, we will be discussing current initiatives, progress and challenges to specifying and evaluating imaging performance for automotive applications. We first address objective image quality methods, as developed for image capture systems. Several of these methods have been adapted in emerging standards for, e.g., automotive (ADAS) and machine-vision applications. We describe how and why imaging performance methods are being adopted. Most efforts rely on several ISO-defined methods, e.g., for color-encoding, image resolution, distortion, and noise. While several measurement protocols are similar, the image quality needs can differ. For example, machine vision often emphasizes detector signal and noise characteristics. However, the CPIQ (mobile Imaging) and IEEE P2020 automotive imaging initiatives include attributes due to optical and video performance (e.g., distortion and motion artifacts).