Threshold segmentation method was widely applied in image process and the selection of threshold affected the final results of image segmentation to a large extent. In order to improve the accuracy and the calculation speed of image segmentation, an Otsu threshold segmentation method based on genetic algorithm was offered. According to the threshold and the gray scale values of pixels, the pixels were divided into two categories, and then the genetic algorithm was used to find the maximum variance between clusters and obtain the optimal threshold of segmentation image. The experimental results show that this method can be used to segment the image effectively, which make the basis for image processing and analysis in the next step.
Headlight detection was an important item of vehicle safety testing which main detection contents included light intensity and beam irradiation direction. It was to ensure the safe operation of vehicle at night or in adverse visual conditions. The basic concepts and testing standards of headlight were introduced, and the reasons of high failure rate for headlight detection were discussed. The main error correction methods of vehicle parking position in headlight detection were compared, and their advantages and disadvantages were analyzed. An error correction system of headlight testing measurement data was designed based on machine vision, and the process of system realization was given. It could provide a method to get more accurate measurement results of automobile headlight detecting.
In order to reduce the fuel consumption and emissions of automobile, the engine idle speed control method was studied. The basic concept of engine idle speed and the requirements and strategies of idle speed control were introduced, and the features and structures of CAN bus technology were analyzed. An idle speed control system of automobile engine based on CAN bus was designed which included main control module, front control module and rear control module. The overall structure, hardware design and software implementation of the system were given. The system can realize the desired functions, and it has certain application value.
In order to improve the accuracy of some items in vehicle inspection, the extraction method of automobile center axis based on image processing technologies was studied. The commonly used methods of detecting the center axis of automobile were introduced, including approximation method and linear fitting method, which advantages and shortcomings were analyzed. The center axis detection method based on centroid method was proposed. The mass center of automobile outline was gotten based on the binary image. By detecting the nearest two points in the outline fitting line from the center, the center axis of automobile was gotten. This method can greatly reduce the calculation amount and have certain application value.
Modern medical diagnose has higher demand for image archiving and communication, the medical image display technology is mainly studied under the Windows platform. According to the analysis of the DICOM 3.0 standards and file formats, the general idea of the conversion from DICOM format to BMP format is proposed. Based on the object-oriented programming idea, a format conversion class called CDicomConvert is designed by using Visual C++. The class encapsulates many data and methods for DICOM image processing, and the class CDib is also improved. The result of the software running shows that it can convert the DICOM file to BMP format, and the medical image can be displayed under Windows.
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