Standardized Judgment Method of Shooting Training Action Based on Digital Video Technology

Aiming at the difficulty of standardizing the action of basketball shooting training, a new method of standardizing the action of basketball shooting training is proposed based on digital video technology. The digital video signal representation, video sequence coding data structure, and video sequence compression coding method are analyzed, and the pixels of basketball shooting training action position space are sampled to collect basketball shooting training images. The time difference method is used to extract the movement target of basketball shooting training from a digital video sequence. Based on digital video technology, the initial background image is estimated, and the update rate is introduced to update the background estimation image. According to the pixel value sequence of the basketball shooting training image, the pixel model of the basketball shooting training image is defined and modified. By judging whether the defined pixel value matches the background parameter model, the standardization of shooting training can be realized. The experimental results show that the proposed method has good stability, high precision, and short time in determining the standardization of shooting movement, can correct the wrong shooting movement in real time, and can effectively guide basketball shooting training.

Ship Detection via Dilated Rate Search and Attention-Guided Feature Representation

Due to the complexity of scene interference and the variability of ship scale and position, automatic ship detection in remote sensing images makes for challenging research. The existing deep networks rarely design receptive fields that fit the target scale based on training data. Moreover, most of them ignore the effective retention of position information in the feature extraction process, which reduces the contribution of features to subsequent classification. To overcome these limitations, we propose a novel ship detection framework combining the dilated rate selection and attention-guided feature representation strategies, which can efficiently detect ships of different scales under the interference of complex environments such as clouds, sea clutter and mist. Specifically, we present a dilated convolution parameter search strategy to adaptively select the dilated rate for the multi-branch extraction architecture, adaptively obtaining context information of different receptive fields without sacrificing the image resolution. Moreover, to enhance the spatial position information of the feature maps, we calculate the correlation of spatial points from the vertical and horizontal directions and embed it into the channel compression coding process, thus generating the multi-dimensional feature descriptors which are sensitive to direction and position characteristics of ships. Experimental results on the Airbus dataset demonstrate that the proposed method achieves state-of-the-art performance compared with other detection models.

A Fast Image Compression Algorithm Based on Wavelet Transform

With multimedia becoming widely popular, the conflict between mass data and finite memory devices has been continuously intensified; so, it requires more convenient, efficient and high-quality transmission and storage technology and meanwhile, this is also the researchers’ pursuit for highly efficient compression technology and it is the fast image transmission that is what people really seek. This paper mainly further studies wavelet analysis and fractal compression coding, proposes a fast image compression coding method based on wavelet transform and fractal theory, and provides the theoretical basis and specific operational approaches for the algorithm. It makes use of the smoothness of wavelet, the high compression ratio of fractal compression coding and the high quality of reconstructed image. It firstly processes the image through wavelet transform. Then it introduces fractal features and classifies the image according to the features of image sub-blocks. Each class selects the proper features. In this way, for any sub-block, it only needs to search the best-matched block in a certain class according to the corresponding features. With this method, it can effectively narrow the search in order to speed up coding and build the relation of inequality between the sub-block and the matching mean square error. So, it can effectively combine wavelet transform with fractal theory and further improves the quality of reconstructed image. By comparing the simulation experiment, it objectively analyzes the performance of algorithm and proves that the proposed algorithm has higher efficiency.

A Syllable-Based Technique for Uyghur Text Compression

To improve utilization of text storage resources and efficiency of data transmission, we proposed two syllable-based Uyghur text compression coding schemes. First, according to the statistics of syllable coverage of the corpus text, we constructed a 12-bit and 16-bit syllable code tables and added commonly used symbols—such as punctuation marks and ASCII characters—to the code tables. To enable the coding scheme to process Uyghur texts mixed with other language symbols, we introduced a flag code in the compression process to distinguish the Unicode encodings that were not in the code table. The experiments showed that the 12-bit coding scheme had an average compression ratio of 0.3 on Uyghur text less than 4 KB in size and that the 16-bit coding scheme had an average compression ratio of 0.5 on text less than 2 KB in size. Our compression schemes outperformed GZip, BZip2, and the LZW algorithm on short text and could be effectively applied to the compression of Uyghur short text for storage and applications.

Computational Intelligence in the Reversible Data-Hiding Processes Using Radon Transform

Data hiding has emerged as a major research area due to the phenomenal growth in internet and multimedia technologies. Securing data transmitted over the internet becomes a challenging issue caused in digitization and networking over the past decade. Data hiding schemes have been adopted to protect digital media content which involves confidential data such as text, video, audio, images, and compression coding. A good reversible data hiding scheme is characterized by the possession of attributes like reversible, imperceptible, high payload capacity, and robustness. By reversible, it's meant that the extraction of the payload as well as the restoration of the host image perfectly from the stego image. Secondly, the imperceptible stego image resemblance against the cover/host image. Finally, robustness counts for the ability to sustain the secret payload against both intentional and unintentional attacks; it has been observed that all the proposed algorithms are more robust and reversible against various attacks in lower bit error rate and higher normalization coefficient.