Applied Mechanics and Materials Vols. 631-632

Abstract: We adopt a fast image texture recognition technology to identify whether an image for texture image, Then we extract the texture feature for image texture, and to extract the color features for Non-texture images, By classifying different types of image retrieval to improve retrieval efficiency. The experimental results show that, this method of the rapid texture recognition technology can greatly improve the accuracy of image retrieval, and it has a great effect in terms of speed.

Abstract: In this paper, a stacked denoising auto-encoder architecture method with adaptive learning rate for action recognition based on skeleton features of human is presented. Firstly a Kinect is used for capturing the skeleton images and extracting skeleton features. Then an adaptive stacked denoising auto-encoder with three hidden layers is constructed for unsupervised pre-training. So the trained weights are achieved. Finally, a neural network is constructed for action recognition, in which the trained weights are used as the initial value, covering the random value. Based on the experimental results from the Kinect dataset of human actions sampled in experiments, it is clear to see that our method possesses the better robustness and accuracy, compared with the classic classification methods.

Abstract: This paper introduces a HVS Weighted color features’ extract method. Firstly, we split the image into sub-blocks and draw the color feature consists of dominant colors in each sub-block. Then weighting the gained color features by making use of Human Visual System. So we can obtain the weighted dominant color feature. Comparing with traditional histogram method and split blocks dominant color method, the experiment results show that the proposed algorithm based on weighted dominant color feature has better retrieval precision.

Abstract: The text introduces the research status of depth image in the pattern recognition and the application in the body recognition. Aiming at the problem that the image recognition shot by common camera has declined performance under the factors of illumination, posture, shielding, and the like, the body parts are distinguished and judged by taking Kinect equipment promoted by Microsoft as the platform, analyzing the features of the depth picture obtained by the Kinect camera and putting forwards to the local gradient features of comprehensive point features and the gradient features; and the elbow is taken as the example to argue simply .

Abstract: This paper firstly studies the image color features based on wavelet territory. We introduce a color features’ extract method based on HSI low-frequency subband color features after partition. Firstly, according to the image attention from human eyes, we split the image into sub-blocks. Then extract HSI low-frequency subband color features of each sub-block after wavelet transform, and we can obtain the image color features by weighting. Comparing with traditional histogram method, the experiment results show that the proposed algorithm based on weighted dominant color feature has better retrieval precision.

Abstract: Although class D amplifier has the merits of high efficiency, a little heat and small Bulk, its distortion is larger than linear counterparts due to switching behaviour of power transistors. Its principle and several new pivotal control technologies were presented in this paper. In this way, efficiency of 90% can be achieved and the degree of the distortion can be less than 0.4%.

Abstract: This paper is devoted to an English Pronunciation training system on the Android platform with functions like English transcription, word pronunciation demonstration, listening and repeating, pronunciation comparison, grading, pronunciation feedback and correction. The training system is designed and developed in line with the characteristics of Android operation system, giving full play to the advantages of Android platform by calling the relevant functions of function interface and components to improve the development efficiency of the system. The system is of high real-time and reliability with a series of multimedia techniques like the pronunciation mouth video-based animation, internal mouth structure figure, pronunciation guidance of mouth and tongue positions, and can effectively guide the learners to learn and practice English pronunciation.

Abstract: Synthetic aperture radar (SAR) is a sort of microwave remote sensing imaging radar, which has much advantage. But it also has much shortcoming, such as speckle noise and directional sensitivity. Reducing impact of them to SAR image processing and applications is an important content, especially, extracting features for ground objects. Contourlet transform is a kind of multi-scale and multi-direction transform theory, and it is a sparse representation mode, too. This paper mainly studied Contourlet transform theory and its decomposition structure, and then it was used to extract SAR image features. Experimental results show that Contourlet transform can effetely extract SAR image features.

Abstract: Compressive Sampling Matching Pursuit (CoSaMP) is a new iterative recovery algorithm which has splendid theoretical guarantees for convergence and delivers the same guarantees as the best optimization-based approaches. In this paper, we propose a new signal recovery framework which combines CoSaMP and Curvelet transform for better performance. In classic CoSaMP, the number of iterations is fixed. We discuss a new stopping rule to halting the algorithm in this paper. In addition, the choice of several adjustable parameters in algorithm such as the number of measurements and the sparse level of the signal also will impact the performance. So we gain above parameters via a large number of experiments. According to experiments, we determine an optimum value for the parameters to use in this application. The experiments show that the new method not only has better recovery quality and higher PSNRs, but also can achieve optimization steadily and effectively.

Abstract: This paper proposed a new method of feature description for insulator species recognition. A method of calculating the difference was defined. The three component value matrixes of an image in HSI space were converted to difference value matrixes successively. Then the difference value, shape and angle features of each region and each color were described. Experiments showed that the proposed method can be applied to describe the actual aerial images, and achieved the recognition of insulator species.