This paper presents an improved Oriented Features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) algorithm named ORB using three-patch and local gray difference (ORB-TPLGD). ORB takes a breakthrough in real-time aspect. However, subtle changes of the image may greatly affect its final binary description. In this paper, the feature description generation is focused. On one hand, instead of pixel patch pairs comparison method used in present ORB algorithm, a three-pixel patch group comparison method is adopted to generate the binary string. In each group, the gray value of the main patch is compared with that of the other two companion patches to determine the corresponding bit of the binary description. On the other hand, the present ORB algorithm simply uses the gray size comparison between pixel patch pairs, while ignoring the information of the gray difference value. In this paper, another binary string based on the gray difference information mentioned above is generated. Finally, the feature fusion method is adopted to combine the binary strings generated in the above two steps to generate a new feature description. Experiment results indicate that our improved ORB algorithm can achieve greater performance than ORB and some other related algorithms.

The Oriented FAST and Rotated BRIEF (ORB) algorithm has the problem that the extracted feature points are overconcentrated or even overlapped, leading to information loss of local image features. A homogenized ORB algorithm using dynamic thresholds and improved quadtree method is proposed in this paper, named Quadtree ORB (QTORB). In the feature point extraction stage, a new dynamic local threshold calculation method is proposed to enhance the algorithm’s ability to extract feature points at homogeneous regions. Then, a quadtree method is improved and adopted to manage and optimize feature points to eliminate those excessively concentrated and overlapping feature points. Meanwhile, in the feature points optimization process, different quadtree depths are set at different image pyramid levels to prevent excessive splitting of the quadtree and increase calculation speed. In the feature point description stage, local gray difference value information is introduced to enhance the saliency of the feature description. Finally, the Hamming distance is used to match points and RANSAC is used to avoid mismatches. Two datasets, namely, the optical image dataset and SAR image dataset, are used in the experiment. The experimental result shows that, considering accuracy and real-time efficiency, the QTORB can effectively improve the distribution uniformity of feature points.

In view of the test and maintenance requirements of the mechanical and electrical system of a certain type of aircraft, a kind of portable mechanical and electrical system test instrument for a certain type of aircraft is designed and realized. This test system enables to collect and display the states of mechanical and electrical subsystems of a certain type of aircraft, and can output corresponding excitation to the device interface of the aircraft electrical system measured, collect relevant data, verify the system function and detect the fault mechanical and electrical system. The system uses the Compact-DAQ modular data acquisition system of US NI company as the core, the analog and discrete acquisition board as the signal acquisition, the analog output boards and self-made discrete output module as the excitation output signal source, with the cooperation of the self-made switching matrix, to achieve the functions of the signal acquisition and real-time display, the storage and playback of data and the output of excitation signal. Test results show that the test system has the advantages of stable performance, high reliability, high testing efficiency, simple operation, and has high versatility and portability, which can meet the needs of field test.