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As with the huge number of deaf-mute people in China is of concern, there is a growing need to integrate them into mainstream society through the use of efficient sign language processing technologies. Sign language processing entails the systematic recognition and translation of sign language images/videos to text or speech. This survey provides an overview of the most important work on Chinese sign language recognition and translation, discussed its classification, highlights the features explored in sign language recognition research, presents the datasets available, and provides trends for the future research.

Road detection is a fundamental component of autonomous driving systems since it provides validspace and candidate regions of objects for driving decision. The core of roaddetection methods is extracting effective and discriminative features. Sincetwo‐dimensional (2D) and 3D features are complementary, the authors propose arobust multi‐feature combination and optimisation framework for stereo imagepairs, called Feature++. First, several 2D and 3D features such as Gabor andplane are, respectively, extracted after the generation of 2D super‐pixel and a3D depth image from stereo matching. Second, the combined features are fed intoa three‐layer shallow neural network classifier to decide whether a super‐pixelis road region or not. Finally, the classified results are further refined usingfully connected conditional random field (CRF), taking the content informationinto consideration. We extensively evaluate the performance of four 2D features,four 3D features, and their combinations. Experiments conducted on the KITTIROAD benchmark show that (i) the combinations of 2D and 3D features greatlyimprove the road detection performance and (ii) using CRF as a refinement stepis necessary. Overall, their proposed ‘Feature + +’ method outperforms mostmanually designed features, and is comparable with state‐of‐the‐art methods thatare based on deep learning methods.

Wavelet analysis based on image enhancement technique is only applicable to black-and-white image, and pseudo-color image processing technology cannot adequately deal with some of the details information of the image. In this paper, an enhanced approach of remote sensing image based on orthogonal wavelet analysis and pseudo-color image processing is presented. Enhanced remote sensing image has been greatly improved in both visual effects and noise characteristics. The method is simple yet flexible with less calculation. Moreover, the proposed method also has the advantages of faster computing speed and operating feasibly and so on. It has great potential in research and application of remote sensing image enhancement.