Wireless Video Sensor Networks (WVSNs) are becoming one of the most used technologies for surveillance and livestock monitoring. They are composed of small embedded video and camera motes that capture video frames periodically and send them to a specific node called a sink. Sending all the captured images to the sink consumes a lot of energy on every sensor and may cause a bottleneck at the sink level. Energy consumption and bandwidth limitation are two important challenges in WVSNs because of the limited energy of nodes and the medium scarcity. The first one is related to the sensing and transmission modules of the sensor node. The higher the frame rate and the number of frames sent, the more energy is consumed. The second one is related to the transmission module of the sensor node, the greater the number of frames sent on the network the more bandwidth is used. In this paper, FRABID, a joint data reduction, and frame rate adaptation on sensing and transmission phases mechanism is introduced. This approach reduces the number of sensed frames based on a similarity method. The aim is to adapt the number of sensed frames based on the degree of difference between two consecutive sensed frames in each period. This adaptation technique maintains the accuracy of the video while capturing frames holding new information. This approach is validated through simulations using real data-sets from video sensors [3]. The results show that the amount of sensed data is reduced by more than 70% compared to a recent algorithm in [2], while guaranteeing the detection of all the critical events at the sensor node level.