The invention discloses a multidirectional water meter reading area detection algorithm employing a full convolution neural network, and the algorithm comprises the following steps: S1, obtaining training data which comprises a water meter image and reading region mark information; S2, training the full convolution neural network through the mark information for the extraction of multilayer cascading features, and obtaining a multichannel characteristic image; S3, carrying out the sliding window scanning of the characteristic image, taking a full connection neural network as a classifier and a regression device, and screening out a rectangular candidate window of a water meter reading region preliminarily; S4, extracting the features of a corresponding region in the characteristic image according to the region position information of the candidate window, taking a second full connection neural network as the classifier and the regression device, and obtaining the center, length, width and angle information of the water meter reading region; S5, finally obtaining a detection result of the multidirectional water meter reading area in a manner of a rotating rectangular frame. The algorithm is accurate, robust and practical.