Abstract: A method and a system for detecting a scene text are provided. The method includes: acquiring a scene text picture in a preset manner, pre-processing the acquired scene text picture, detecting the pre-processed scene text picture with a training model for scene text detection, and acquiring a detection result. Accordingly, the method and the system have an original PSENet (Progressive Scale Expansion Network) backbone network ResNet (Deep Residual Network) is replaced with a rich feature structure network (i.e. Res2NeXt (Combination of Res2Net and ResNeXt)) to improve a network feature extraction capability, thereby increasing a text detection precision of the network; mixed pooling is added at an appropriate location in the backbone network to acquire useful context information by performing pooling operations of different kernel shapes and capture long and short distance dependency relationships between different locations, thereby further increasing the text detection precision of the network.

Abstract: A method and a system for detecting a scene text are provided. The method includes: acquiring a scene text picture in a preset manner, pre-processing the acquired scene text picture, detecting the pre-processed scene text picture with a training model for scene text detection, and acquiring a detection result. Accordingly, the method and the system have an original PSENet (Progressive Scale Expansion Network) backbone network ResNet (Deep Residual Network) is replaced with a rich feature structure network (i.e. Res2NeXt (Combination of Res2Net and ResNeXt)) to improve a network feature extraction capability, thereby increasing a text detection precision of the network; mixed pooling is added at an appropriate location in the backbone network to acquire useful context information by performing pooling operations of different kernel shapes and capture long and short distance dependency relationships between different locations, thereby further increasing the text detection precision of the network.

Abstract: A 3D-HEVC inter-frame information hiding method based on visual perception includes steps of information embedding and information extraction. In the step of information embedding, the human visual perception characteristic is considered, stereo salient images are obtained by a stereo image salient model, and the stereo salient images are divided into salient blocks and non-salient blocks with an otsu threshold. The coding quantization parameters are modified according to different modulation rules for different regions. Then, based on the modified quantization parameters, the coding-tree-units are coded to complete the information embedding. In the step of information extraction, no original video is needed, no any side information needs to be transmitted, and the secret information can be blindly extracted.

Abstract: A high dynamic range image information hiding method includes embedding secret information and extracting the secret information. The step of embedding secret information includes obtaining three channel values of every pixel in an original high dynamic range image; according to every channel value and corresponding 5-bit exponent of every pixel, determining an embedding significance bit of the information to be embedded in every channel value of every pixel; embedding information into every channel value of every pixel; and obtaining a high dynamic range image embedded with the secret information.

Abstract: A high dynamic range image information hiding method includes embedding secret information and extracting the secret information. The step of embedding secret information includes obtaining three channel values of every pixel in an original high dynamic range image; according to every channel value and corresponding 5-bit exponent of every pixel, determining an embedding significance bit of the information to be embedded in every channel value of every pixel; embedding information into every channel value of every pixel; and obtaining a high dynamic range image embedded with the secret information.

Abstract: A 3D-HEVC inter-frame information hiding method based on visual perception includes steps of information embedding and information extraction. In the step of information embedding, the human visual perception characteristic is considered, stereo salient images are obtained by a stereo image salient model, and the stereo salient images are divided into salient blocks and non-salient blocks with an otsu threshold. The coding quantization parameters are modified according to different modulation rules for different regions. Then, based on the modified quantization parameters, the coding-tree-units are coded to complete the information embedding. In the step of information extraction, no original video is needed, no any side information needs to be transmitted, and the secret information can be blindly extracted.