Automation of complicated underwater tasks require acoustic image based object recognition. This paper presents an acoustic image based real-time object recognition system. We proposed an acoustic image predictor to estimate an object's shape in advance. Depending on the acoustic camera's position, the predictor generates optimal template for recognition. The proposed method is implemented in our autonomous marine vehicle. For real-time processing, efficient recognition strategies are addressed. The vehicle detects an object and localizes it for recognition. In the detection process, the acoustic image's specific characteristics are used as the detection cues. In the localization process, the vehicle's horizontal and vertical positioning strategies are described. Efficient template generation method to minimize computing power is addressed. This realizes real-time recognition using the vehicle. To estimate the proposed system's accuracy and reliability, a recognition test was carried out in the field. The vehicle successfully recognized two different objects with high accuracy.