As the industrial basic part，the gears machining accuracy has a significant impact on the overall accuracy and reliability. It is one of the important factors that determine the quality of our country's manufacturing industry. In order to improve the detection accuracy and detection speed of gears, a gear lead precision detection method based on laser ranging is proposed. And the gear lead detection system is also developed on the basis of this method. Because of the laser measuring advantages in terms of metal and reflective objects, the laser is selected as the measuring light source. The relative coordinate information of the gear measuring point is obtained using laser triangulation method. In order to get the information of all parts of the gear, by the circular motion of flotation turntable and the lift linear motion of precision electric lift table, data scanning of the gear lead can be completed. In order to obtain absolute coordinates of the gear, the measuring calibration algorithm is proposed to calculate the positional relationship between the sensor and the gear pitch circle. The results show that the proposed measuring method can meet the requirements of high-precision and Non-destructive testing in industry and can be able to classify the gears. And the proposed method can be able to apply to high-precision dimensional inspection system of other metallic reflective objects.

A cross-polarization scheme and vertical multi-layer structure is presented to filter out the excitation light from the emission spectrum of fluorescent dyes using green organic light emitting diode as light source and a linear charge coupled device as intensity detector. Micro lens array film was affixed on glass base of organic light emitting diode in order to improve the incident intensity. Electrophoretic separation were performed with Rhodamine B as sample solution under the optimal parameters including integral time of CCD, diameter of PDMS micro lens and two polarizers’ polarization angle in the detection system.

In the laser scanning system based on Articulated Arm Coordinate Measuring Machine (AACMM), the extraction accuracy of laser stripe center and using time directly affects the measuring accuracy and real-time response capability of the whole system. Integration and improvement over the existing algorithms at home and abroad, an optimal threshold method and improved Sobel operator and light strip repaired algorithm are used to complete the light crude extraction with picking up ten pixels. Experiments show that, in the 350 mm × 350 mm measuring range, the measuring error is less 50 μm, the extraction time is less 31 ms, and it can meet the requirements of real-time online system.

This article refers to the test for refractive index of high-index material (1.80＜nd＜2.00)by using a V-prism test method, and the index liquid which nd is equal to the sample need to be dropped into the linking face between V-prism and sample, in order to eliminate the sample angle of 90° processing deviation . Since the highest refractive index is only at 1.78 of existing index liquid, great nd deviation between the tested data and true value comes out in this test, and the greatest refractive index deviation has reached to 20×10-5. Now we have found out the discrepancy principle of high-index sample test data by the light refractive route research of V-prism test method. By means of calculating refractive index deviation to compensate test data, make the deviation of compensated refractive index reduce to ±4×10-5. Therefore, the measuring accuracy (±5×10-5) of high-index glass is ensured by our V-prism method.

Through the subtraction of two digital holographic wrapped phases for different wavelengths, it yields a beat phase image corresponding to an equivalent wavelength to remove the phase wrapping. By comparing the beat phase image with any recoding wavelength, the position and multiple of the single wavelength phase jump are confirmed. Hence, the wrapped phase in single wavelength phase is wrapped and the phase noise is kept fixed. Simulation and experimental results demonstrate the measure error induced by the phase noise can be reduced to 2Λ/λm. An optical microstructure element surface is measured by the proposed digital holography with dual wavelength of 650 nm and 632.8 nm. The measured optical element is produced with Fast Tool Servo (FTS). The unwrapped phase image of machining mark on the surface of microstructure element is acquired clearly. The equivalent wavelength is 0.024 mm. Then, the three dimensional data of the microstructure profile respectively in high frequency and low frequency regions are obtained by frequency filtering. The roughnesses corresponding to different frequency region are 33.2 nm, 19.3 nm and 23.4 nm respectively. The affecting factors for different machining mark are analyzed. The cutting parameters of the FTS are also deduced.

Based on the classical numerical reconstruction method, the reconstructed image according to different depth section of the three-dimensional object would be disturbed by the twin image and out-of-focus section image. Therefore, a numerical reconstruction method according to compressive sensing theory for a single off-axis Fresnel hologram is proposed to achieve tomographic imaging. First, the adaptive filtering method is applied to the hologram to eliminate the twin image. And then, based on the compressive sensing theory, different depth section images can be reconstructed with the background out-of-focus object inhibited. The numerical simulation and digital holography experiment employing test targets are performed to demonstrate the feasibility and validity of the method.

Using EVA hot melt adhesive film, an epoxy resin prepared photopolymer holographic memory card was prepared, and the preparation process is simple. First, prepared epoxy photopolymer temperature tests were conducted and a new process for the preparation of the holographic storage medium has been proposed. Then, its 532 nm wavelength holographic characteristics were studied. The holographic memory card with a high temperature (≥60 ℃), easy to scratch characteristic diffraction efficiency ≥50%, moderate exposure sensitivity, can be angular multiplexing holographic storage. The holographic storage card for long-term storage tests has been conducted and the cartridge shelf life results ≥ 6 months have been drawn.

In order to suppress the ringing and jaggy artifacts during the super-resolution image reconstruction process, an image super-resolution algorithm with multiple regularized terms is proposed. Firstly, the image degradation model is given and the image reconstruction constraint item is analytically derived. The high-resolution image can be generated by using the reconstruction constraint item, which will have jaggy and ringing artifacts. In order to solve this problem, the autoregression model and filters prior are invented to regularize the reconstruction process. The autoregression model is used to restore the local image details and the adaptive parameters of the autoregression model can be generated through the natural cluster sets. Meanwhile, the filters prior are used to force the edges of high-resolution image to be sharp. Finally, the experimental results show that our algorithm outperforms other competing algorithms in terms of both quantity and quality.

In order to quickly and efficiently provide detailed information of goods to customers, we design a new label, as well as shopping navigation system which can be used in large stores. The system records the image acquisition module, a tag identifying module, a database, the transmission module, and the position of the navigation module. Image acquisition system recording module is taken by commodity label information. Label recognition module for the design of the new label recognition processing, and retrieval and identification results match the product information from the database module. Transmission module via data lines and wireless transceiver technology navigate to the location information transmission module. Navigation module indicates the position of the actual position of the product, and shows that the product -specific information. Hundreds of images experiments were carried out first to correctly identify the exact rate of 90%. If the first identification fails, you can take pictures by simply re-adjust the recognition results. Experimental results show that the new shopping navigation system based on label recognition to solve the traditional bar codes and 2D codes need to pave the identification and location of the bar code is not obvious. The smaller the areas, the need at a very close distance to identify defects that can assist the customer quickly find their favorite items.

The existing local feature descriptors, such as SURF and BRISK, either cannot meet the real-time or have poor performance, so the paper presents a novel descriptor SURF-BRISK. The descriptor detects the Key-points by SURF and computes the descriptor by BRISK. Firstly, our method is used to do feature matching. Then RANSAC robust estimation is performed to eliminate the wrong matched points. Finally, location of object is based on the affine transform’s six parameters which are calculated by the correct matches. Experiments show that SURF-BRISK feature descriptor is not only real-time and robustness, but also achieves good results in object location.

This paper presents an iterative filtering method on the de-noising of Synthetic Aperture Radar (SAR) image based on block matching. Firstly, it makes use of the similarity among the image blocks to conduct block matching and to construct a three-dimensional matrix of the similar image block. And then, it performs iteration filtering to remove speckle noise in transform domain among similar image blocks, so that we can obtain the basic estimation denoised image after reconstruction by weighted average. Finally, it performs block matching on the basic estimate denoised image, and filters in the similar image blocks and among the similar image blocks to get the final denoised image by 3-D experience filter. Experiments show that the proposed method can effectively suppress speckle noise of SAR image, while preserving better the edge and texture information.

In view of the current situation that the detection method is inefficient and low efficiency, this paper proposes a fast and efficient detection method for irregular shape. In this method, matching feature points between the actual captured image and the reference model are firstly used to find the contour mapping of the location, thereby solve their perspective transformation parameters. Then, extract edge of the irregular shape in the target image and transform the extracted edge points using the perspective transformation parameters. Finally, compared with the data, this method, non-contact, less equipment, low environmental impact, object is only the photographic image, and fast detection speed is suitable for all kinds of irregular shape. Standard experimental analysis shows that the method has high detection precision with 0.2 mm and good efficiency.

According to the characteristics of ultrasound images with low contrast and SPECT images with blurred boundary, combining the theory of multi-scale geometric analysis with single scale sparse representation, an image fusion algorithm based on Shearlet transform and sparse representation is proposed. Firstly, the Shearlet transform is used to decompose the registered source images, thus the low frequency sub-band coefficients and high frequency sub-band coefficients can be obtained. The low frequency sub-band coefficients with lower sparseness are used to train the dictionary and the sparse representation coefficients are calculated by the trained dictionary, and the fusion rule of the sparse representation coefficients is used to select the larger energy. The high frequency sub-band coefficients are fused by the region sum modified laplacian. Finally, the fused image is reconstructed by inverse Shearlet transform. The experimental results demonstrate that the proposed method outperforms the multi-scale methods and the methods of sparse representation in single scale in term of visual quality and objective evaluation.

We have proposed a design of silicon based germanium metal-semiconductor-metal (MSM) photodetectors with asymmetric area electrodes based upon its dark current suppression mechanism. The influence of electrode structure on the dark current are simulated using ATLAS software. And the dark current of the samples is reduced to μA scale in experiment. Effective dark current suppression and performance improvement in silicon based germanium MSM photodetectors are then demonstrated.

In view of this phenomenon that the output signal precision of the absolute type encoder is not stable, which relies on artificial debugging, a set of output signal error automatic compensation system is designed. The system establishes the connection with the server by TCP communications, and acquired the parameters needing to debug. Then analyze the reason for leading to the signal error. With the high-precision encoder estimated value as the goal of learning, it establishes Radial Basis Function neural network mode, which would form the output value of the minimum error as the ideal input value of the fine adjustment. In this way, it might realize errors minimizing. After the calibration data, write to the encoder chip. Experiments show that, the automatic system is used to compensate each code channel of the value of amplitude, phase and offset, which compared with the manual debugging, and the signal error is reduced on average by 49.82%.