Latency time and hardware compactness are two important problems of real-time image processors for moving object tracking. We have developed a compact self-contained real-time image processor that is implemented on a single double-height VME board. The processor can execute major processing steps for moving object tacking during a single video field time. These steps are preprocessing, binarizing, labeling, feature extraction, and feature evaluation. We can obtain sorted feature vectors simultaneously when image data is read out from a sensor. Here a feature vector represents areas, centroid, and maximum intensity of each connected region in a binarized image. Some conventional image processors can execute the above steps individually in real-time and thread some steps in a pixel pipeline manner. However it is difficult to integrate feature extraction and feature evaluation in a pixel pipeline path. For real-time execution of all steps we focused on new architecture particularly for the latter three steps. To minimize the hardware we have developed three ASICs: labeler, feature accumulator, and sorter. To make our processor self-contained and scalable, it has an on- board micro processor, a digital video bus interface, and an RS232C port, and it is VME compatible in bus interface and mechanical dimension.