It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.
BackgroundCervical disc replacement (CDR) has been widely used to restore and maintain mobility and function of the treated and adjacent motion segments. Posterior longitudinal ligament (PLL) resection has been shown to be efficient in anterior cervical decompression and fusion. However, less is known about the biomechanical effect of PLL removal versus preservation in cervical disc arthroplasty.Material/MethodsThree motion segments of 24 ovine cervical spines (C2–C5) were evaluated in a robotic spine system with axial compressive loads of 50 N. These cervical spines were divided in three groups according to the following conditions: (1) intact spine, (2) C3/C4 CDR with the Prestige LP prosthesis and PLL preservation, and (3) C3/C4 CDR with the Prestige LP prosthesis and PLL removal. The ranges of motion (ROMs) were recorded and analyzed in each group.ResultsThe C3/C4 ROM in group 3 (CDR with PLL removed) increased significantly in flexion-extension and axial rotation compared with group 1 (intact spine). Moreover, in flexion-extension, the mean total ROM was significantly larger in group 3 than in group 1. All the ROM observed in group 2 (CDR with PLL preserved) did not significantly differ from the ROM observed in group 1.ConclusionsCompared with intact spines, CDR with PLL removal partly increased ROM. Moreover, the ROM in CDR with PLL preservation did not significantly differ from the ROM observed in intact spines. The PLL appears to contribute to the balance and stability of the cervical spine and should thus be preserved in cervical disc replacement provided that the posterior longitudinal ligament is not degenerative and the compression can be removed without PLL takedown.
English feature recognition has a certain influence on the development of English intelligent technology. In particular, the speech recognition technology has the problem of accuracy when performing English feature recognition. In order to improve the English feature recognition effect, this study takes the intelligent learning algorithm as the system algorithm and combines support vector machines to construct an English feature recognition system and uses linear classifiers and nonlinear classifiers to complete the relevant work of subjective recognition. Moreover, spectral subtraction is introduced in the front end of feature extraction, and the spectral amplitude of the noise-free signal is subtracted from the spectral amplitude of the noise to obtain the spectral amplitude of the pure signal. By taking advantage of the insensitivity of speech to the phase, the phase angle information before spectral subtraction is directly used to reconstruct the signal after spectral subtraction to obtain the denoised speech. In addition, this study uses a nonlinear power function that simulates the hearing characteristics of the human ear to extract the features of the denoised speech signal and combines the English features to expand the recognition. Finally, this study analyzes the performance of the algorithm proposed in this study through comparative experiments. The research results show that the algorithm in this paper has a certain effect.
In this article, a level ruler Precision Verification System program of the mobile-camera image processing technology that is based on the camera mobile image processing technology is proposed, as a result of the research for the existing barcode type level ruler verification system and a high-precision grating sensor system hardware structure is also built. Secondly, we calculate the uncertainty of the system, and at last do the system stability test that the results show that the system achieves the test requirements.
On the barcode type level existing ruler verification system research, proposed a camera mobile image processing technology based on the level ruler of precision calibration system, builds a detection sensor system with high precision grating, realizes automatic acquisition level ruler barcode image, method of application without barcode image with barcode image subtraction the preliminary processing of image acquisition, eliminate the influence of background light on the image acquisition, the uncertainty of the calibration system of the theoretical calculation and experimental verification, the results show that the system achieves the test requirements.
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