Aiming at the problem that the color image with more detailed textures is not highly segmented in the image segmentation process, a PKGC image segmentation method based on improved edge detection difference ratio is proposed. The method first constructs an energy function by using a parametric kernel graph cutting algorithm. Then, the value of the three-channel RGB edge detection ratio of the color image is used to change the constant balance factor in the energy function to change the ratio of the data item and the boundary smoothing term in the energy function, so that the image segmentation effect is optimal. The segmentation results of different experimental show that the improved paper method has better segmentation precision and better segmentation of texture details for complex images.

Fisheye lens had the characteristics of shorter focus and large field,but fisheye images were distorted.Current fisheye distortion correction algorithms had some problem,such as,taking point from the scene was approximate,fitting process was complex,the computational cost was large and the real-time character could not be guaranteed.In this paper, firstly,obtain the formula according to fisheye lens imaging principle.Secondly,get a correction curve from the special points' relationship between the image captured by specific fisheye lens and calibration image. Finally,use the curve to obtain the pixel map table between the fisheye image and the target image. Thus realize the fisheye image distortion's correction. The results show that it is a real-time,fast,accurate fisheye image correction method.

The curved surface projection model in fisheye image correction algorithm is presented. To analyze the causes of distortion in existing models, we establish an ideal surface projection model and compare its surface with the surfaces of existing models. Subsequently, feature points are obtained on the ideal surface according to the relationship of coordinates of fish-eye image points and their ideal three-dimentional (3D) points. Finally, the least square method is used to obtain a quadric surface and presents a quadric surface projection model. The experiment shows that the corrected image of the new model is more similar to the actual scene than the corrected images of previous models.OCIS codes: 100.3008, 100.3010, 140.1135codes: 100.3008, 100.3010, 140. , 140.1488 Fish-eye lenses have extremely short focal length and a very wide field of view (FOV), which is generally close to 180• or even wider [1] . One single fish-eye image can represent a large part of the surroundings. Thus, use of fish-eye lens in detection and survey systems has attracted considerable attention. Wu et al. [2,3] have used fish-eye lens in automatic surveillance.In order to obtain a large FOV, a fish-eye lens uses the "non-similar" imaging thought. As a result, considerable barrel distortion in fish-eye images occurs. In recent years, fish-eye algorithm has been extensively studied. However, fish-eye lens optical transformation is complex and different fish-eye lens have different designs. Hughes et al. [4,5] have evaluated several fish-eye algorithms and found that one algorithm could not fit all types of fisheyes lenses. However, previous work did not address fish-eye lenses with FOV beyond 180• . In this letter, a circular fish-eye lens with a FOV of 186• is used. We adopt the surface projection model to derive the coordinate transformation between the fish-eye image points and their matching scene three-dimensional (3D) points by orthogonal projection. Spherical projection model is used in most applications [6−9] . However, for orthogonal projection, the spherical projection model inherently limits the FOV of the camera to 180• . When the spherical projection model is used to correct the 186• fish-eye lens, the corrected image is marked with barrel distortion. The parabolic projection model proposed by Wang et al. does not have limitations of the spherical projection [10] . However, several pincushion distortions exist in the corrected image of the parabolic projection.According to the imaging theory of fish-eye lens, the surface projection model can simulate the optical transformation process. The corresponding relationship between the target points and the fish-eye image points can be determined by the model, and the fish-eye images can be corrected and transformed to normal plane perspective images.The rules of fish-eye surface projection model are shown in Fig. 1. Suppose that the camera is at the origin of coordinate O, shooting along the Z axis direction. The image taken by fish-eye lens is at the OXY plane and fills a circula...