Because of the advantages of high sampling rate, high-speed image acquisition system is widely used in military, sports, biological and other fields. Unfortunately, just due to its high frame rate, the design risk and design cycle are greatly increased, and the back end image processing is still a challenging problem. In order to solve this problem, an image acquisition system architecture and protocol is proposed in this paper, which divides the image acquisition system into control plane and processing plane. The processing plane is divided into sensor independent layer, cache layer, processing layer and application layer. These layers are physically connected by AXI bus, and the logical relationship between them is as small as possible. Our proposed architecture and protocol effectively reduces the design complexity and design risk, also the design efficiency is greatly improved.
KEYWORDS: Image acquisition, Image processing, Sensors, Field programmable gate arrays, 3D image reconstruction, Image sensors, 3D modeling, 3D acquisition, 3D image processing, Control systems
Laser triangulation is often the best solution for the 3D (three-dimensional) image reconstruction of an object. And its features, such as simple structure, fast reconstruction speed and flexible use make it widely used in 3D reconstruction. However, due to its high image frame rate, huge data, and requiring a large amount of computation for image processing algorithm, it is hard to be applied in embedded system. This paper presents a hardware solution for high-speed image acquisition system which is implemented on Xilinx FPGA. The experimental results indicate that this acquisition system works normally and its performance is steady and reliable, under the extreme conditions with an image resolution of 1280*384 and a frame rate of 9,000. It is still a challenging problem to extract the position information of the light bar in real time. In order to solve this problem, a parallel gray center gravity method based on FPGA is proposed to detect the position of light bar in this paper. Test results show that the proposed method can correctly extract the position information of the light bar in real time when the image frame rate reaches 9,000 frames. The power consumption is only about 4 watts.
We present a quasicommon-path digital holographic microscopy with phase aberration compensation, which is based on a long-working distance objective and can be used for the quantitative characterization of microstructure specimens. The quasicommon-path arrangement makes the holographic system very compact and stable. Meanwhile, the object and reference beams all travel along the same path, which can effectively eliminate the system aberration, and the mirror in the reference arm can be adjusted precisely for the phase tilt compensation. In the experiment, a wafer with orderly patterns and unified height of 180 nm is measured, and its three-dimensional surface topography is obtained. A long-term system stability of 1.39 nm is achieved in measurement with the proposed method.
This paper proposes a model of dual-channel convolutional neural network (CNN) that is designed for change detection in SAR images, in an effort to acquire higher detection accuracy and lower misclassification rate. This network model contains two parallel CNN channels, which can extract deep features from two multitemporal SAR images. For comparison and validation, the proposed method is tested along with other change detection algorithms on both simulated SAR images and real-world SAR images captured by different sensors. The experimental results demonstrate that the presented method outperforms the state-of-the-art techniques by a considerable margin.
Biological cells are usually transparent with a small refractive index gradient. Digital holographic interferometry can be used in the measurement of biological cells. We propose a dual-wavelength common-path digital holographic microscopy for the quantitative phase imaging of biological cells. In the proposed configuration, a parallel glass plate is inserted in the light path to create the lateral shearing, and two lasers with different wavelengths are used as the light source to form the dual-wavelength composite digital hologram. The information of biological cells for different wavelengths is separated and extracted in the Fourier domain of the hologram, and then combined to a shorter wavelength in the measurement process. This method could improve the system’s temporal stability and reduce speckle noises simultaneously. Mouse osteoblastic cells and peony pollens are measured to show the feasibility of this method.
Short-coherence in-line phase-shifting digital holographic microscopy based on Michelson interferometer is proposed to measure internal structure in silicon. In the configuration, a short-coherence infrared laser is used as the light source in order to avoid the interference formed by the reference wave and the reflected wave from the front surface of specimen. At the same time, in-line phase-shifting configuration is introduced to overcome the problem of poor resolution and large pixel size of the infrared camera and improve the space bandwidth product of the system. A specimen with staircase structure is measured by using the proposed configuration and the 3D shape distribution are given to verify the effectiveness and accuracy of the method.
A dual-wavelength common-path digital holographic microscopy is presented to simultaneously improve the phase measurement accuracy and stability. Two laser beams with different wavelength are reflected by the front and back surface of a parallel glass plate to form the composite hologram in the lateral shearing region, and a shorter synthetic wavelength Λ289nm is obtained by calculating the arctangent and product of the two reconstructed complex amplitudes. Thus, phase speckle noise can be reduced in the dual-wavelength numerical reconstruction process, and the phase measurement accuracy and stability can be improved. The experiment results of the peony pollens specimen show the feasibility of the proposed configuration.
Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.
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