The present invention relates to an automatic segmentation method for a breast MRI focus based on inter-frame correlation. The method comprises: reading an MRI image; preprocessing the image, and performing coarse segmentation on the preprocessed image to determine an initial contour of a focus; and by adopting an improved C- V level set model method, performing fine segmentation on a coarsely segmented image that is obtained in the prior step, further refining the tumor contour on the basis of a coarsely segmented contour, and optimizing an obtained finely segmented result by combining inter-frame correlation. The method provided by the present invention has higher accuracy and can better segment the focus.

Automatic segmentation method for breast MRI focus based on Inter-frame correlation

Back-to-back dual-fisheye cameras are the most cost-effective devices to capture 360° visual content. However, image and video stitching for such cameras often suffer from the effect of fisheye distortion, photometric inconsistency between the two views, and non-collocated optical centers. In this paper, we present algorithms for geometric calibration, photometric compensation, and seamless stitching to address these issues for back-to-back dual-fisheye cameras. Specifically, we develop a co-centric trajectory model for geometric calibration to characterize both intrinsic and extrinsic parameters of the fisheye camera to fifth-order precision, a photometric correction model for intensity and color compensation to provide efficient and accurate local color transfer, and a mesh deformation model along with an adaptive seam carving method for image stitching to reduce geometric distortion and ensure optimal spatiotemporal alignment. The stitching algorithm and the compensation algorithm can run efficiently for 1920×960 images. Quantitative evaluation of geometric distortion, color discontinuity, jitter, and ghost artifact of the resulting image and video shows that our solution outperforms the state-of-the-art techniques. 

Efficient and Accurate Stitching for 360° Dual-Fisheye Images and Videos

The invention is suitable for the digital image processing field and provides a fish-eye lens correction method and device and a portable terminal The method comprises the following steps: carrying out distortion correction on a fisheye image through an equidistant projection model to obtain an initial correction image, the image content of which is a calibration board; obtaining all angle pointsof the calibration board from the initial correction image, re-projecting angle point coordinates to the fisheye image to obtain rough angle point coordinate values of the calibration board in the fisheye image, and serving the angle points as feature points in the fisheye image; and carrying out iteration on the feature points in the fisheye image to obtain different parameter values within a preset parameter range, carrying out correction on the fish-eye lens through the equidistant projection model, and serving the parameter value obtained when the deviation amount is minimum as an accurate correction value of the fish-eye lens The fish-eye lens correction method reduces preparation workload in the early stage, and is simple in operation process; a camera does not need to change position and angle; and the fish-eye lens correction method is wide in application range, does not need to set a lot of parameters, is simple to calculate, and meanwhile, realizes an accurate fisheye correction effect

Fish-eye lens correction method and device and portable terminal

In this paper, a linear camera calibration algorithm using one image based on distortion correction is presented. First, this algorithm takes advantage of first-order radial distortion coefficient to correct image primary and then extracts the control points to fit line based on orthogonal distance, getting accurate linear slope. Next, according to the slopes of collinear points, distortion correction index function is established and then all distortions parameters are obtained by optimizing the function using optimization algorithm. Finally, camera can be calibrated linearly with single image that have been corrected based on Zhengyou Zhang algorithm. Distortion parameters, separated from the camera model, do not need to be incorporated into the camera model for multiple repeated calibrations. On the one hand, it solves the problem that Zhengyou Zhang algorithm can not be used in camera systems with a low depth of field. On the other hand, it avoids the instability of solution caused by coupling of distortion parameters, internal parameters and external parameters as well as the complex computations of three LM optimization. A large number of analysis and experiments prove that this algorithm is simple, efficient and has wide application in theory and practice.

Linear Camera Calibration by Single Image Based on Distortion Correction

The invention discloses a fisheye image correction method and device based on coordinate transformation. The method includes: a pixel P' is selected optionally from a fisheye image to serve as a center point to correct the fisheye image, spherical coordinates of the pixel P' at an incident point P of a fisheye semisphere are calculated through the imaging model of a fisheye camera, an optional plane which is parallel to a tangent plane tangent to the fisheye semisphere using the point P as the tangent point is used as the plane where a corrected image is located, the intersection Q of the plane and a ray OP is used as the center point of the corrected image to build the virtual imaging plane of the corrected image, coordinates of corresponding pixels of drawing points in the fisheye image are calculated one by one, and the calculated pixel values of the pixels corresponding to the drawing points in the fisheye image are used as the pixel values of the drawing points in the corrected image to draw in the corrected image so as to obtain the corrected image of the fisheye image. The fisheye image correction method and device based on the coordinate transformation has the advantages that multidirectional real-time correction is performed on the high-definition fisheye camera, and the details of various different areas in the fisheye image can be observed conveniently.

Fisheye image correction method and device based on coordinate transformation

The fisheye camera has been widely studied in the field of robot vision since it can capture a wide view of the scene at one time However, serious image distortion handers it from being widely used To remedy this, this paper proposes an improved fisheye lens calibration and distortion correction method First, an improved automatic detection of checkerboards is presented to avoid the original constraint and user intervention that usually existed in the conventional methods A state-of-the-art corner detection method is evaluated and its strengths and shortcomings are analyzed An adaptively automatic corner detection algorithm is implemented to overcome the shortcomings Then, a precise mathematical model based on the law of fisheye lens imaging is modeled, which assumes that the imaging function can be described by a Taylor series expansion, followed by a nonlinear refinement based on the maximum likelihood criterion With the proposed corner detection and mathematical model of fisheye imaging, both intrinsic and external parameters of the fisheye camera can be correctly calibrated Finally, the radial distortion of the fisheye image can be corrected by incorporating the calibrated parameters Experimental results validate the effectiveness of the proposed method

An improved method for fisheye camera calibration and distortion correction

Tracking target in fisheye camera is getting increasing interest and wide applications. However, due to the special imaging principle of the fisheye lens, videos shoot by fisheye cameras have serious distortion, which brings great interference to the target tracking. In recent years, correlation filters have gained wide attention with its fast and robust characteristics, and have gradually become a type of important method in the field of target tracking. The proposal of the kernelized correlation filter makes a large number of target features available for tracking enhancements. In order to meet the real-time, this paper creatively employs correlation filters for target tracking on fisheye videos. Aiming at the distortion handling, this paper proposes a feature integration with adaptive weight updating and incorporates this feature into the kernelized correlation filtering method. Moreover, this paper makeups a fisheye video data set for evaluating tracking performance. The evaluation results validate that the proposed approach can greatly reduce the impact of deformation on tracking on the basis of the real-time, and also obtain good tracking performance.

Correlation filter based fisheye video target tracking with adaptive weighted feature integration

An image registration method based on SIFT and an authentication mechanism comprises the following steps: firstly, extracting features from a reference image and a to-be-matched image respectively through an improved SIFT algorithm; secondly, using a Harris algorithm to extract corners which can be used as reference points in the matching process, and taking the connecting line of two corners as a reference direction; and thirdly, connecting feature point pairs matched out through the SIFT algorithm with the reference points in corresponding images, calculating the included angle between each connecting line and the reference direction, judging whether a set threshold condition is met by calculating the difference between the included angles, taking the feature point pairs as matching point pairs if the set threshold condition is met, or, judging that the feature point pairs are mismatched. The invention provides an image registration method based on SIFT and an authentication mechanism, which can effectively remove mismatches and prevent correct matching points from being deleted by mistake, and is of high accuracy.

Image registration method based on SIFT and authentication mechanism

The invention relates to an interactive intelligent image segmentation method based on tumor attack. The method comprises the following steps that 1) over-segmentation is carried out on an image to be processed in a simple linear iteration cluster algorithm to obtain corresponding super pixel blocks; 2) color information of each super pixel block is extracted, and the spatially adjacent super pixel block of each super pixel block is found; and 3) an initial segmentation result is obtained by utilizing an iteration energy minimizing segmentation algorithm. According to the method, local information is combined with global information, that a pixel point serves as a processing object in two original methods is replaced, instead, the super pixel serves as the processing object, the frequency in the iteration process is reduced, the speed is higher, and the obtained segmentation result is more stable.

Chengbin Huang

Papers

An improved method for fisheye camera calibration and distortion correction

Correlation filter based fisheye video target tracking with adaptive weighted feature integration

Image registration method based on SIFT and authentication mechanism

Interactive intelligent image segmentation method based on tumor attack