Wei Zhenxing

Bio: Wei Zhenxing is an academic researcher. The author has contributed to research in topics: Image segmentation & Binary image. The author has an hindex of 1, co-authored 1 publications receiving 4 citations.

Three-dimensional entropy based two-dimensional image threshold segmentation method

Abstract: The invention belongs to the field of image processing, and particularly relates to a three-dimensional entropy based two-dimensional image threshold segmentation method The method takes a two-dimensional grayscale digital image as a target, and calculates a local mean image, a local variance image, and a quantification variance image of the target, so as to obtain a three-dimensional histogram through statistics, and as a result, a binary image, namely a final output image, is obtained through an optimal segmentation threshold based on the histogram The method can effectively solve the noise problem in the image, makes the best of image information for image segmentation, and has better processing effect for image details

Moving object detection method based on entropy

Abstract: The invention discloses a moving object detection method based on entropy. Firstly, data of scene graphs are read in, graying processing is carried out on the data, then monitor areas of a scene are marked, difference operation is carried out on every two adjacent frames of gray level images of each monitor area, an optimal threshold of division of the images is determined based on the entropy of the difference operation result, then morphological filter is carried out on the divided images, connected areas are detected, and the detected connected areas are marked; finally, the area of each connected area is calculated, the connected area with the largest area is marked as a moving object, and the moving object is output. Multiple image processing basic methods are applied comprehensively, the technologies in the current computer vision and mode identification fields are introduced into the intelligent monitor field of transmission lines, moving detection of large machines in the transmission line scene is achieved through the related vision information in the transmission line scene, and therefore influence on the transmission line by external force damage is prevented.

Image segmentation method and device and image segmentation method and device applied to slag pieces

Abstract: The invention discloses an image segmentation method and device and an image segmentation method and device applied to slag pieces The method comprises the steps that a grayscale average of a neighborhood of each pixel point is calculated based on a grayscale value of each pixel point in an image of a to-be-tested object; a two-dimensional histogram of the image is constructed according to the calculated grayscale value of each pixel point and the grayscale average of the neighborhood of each pixel point; an optimal segmentation threshold value is calculated according to the two-dimensional histogram of the image; the to-be-tested object in the image is segmented based on the optimal segmentation threshold value to obtain an initial segmented binary image; and the to-be-tested object in the initial segmented binary image is segmented precisely through a watershed method Through the image segmentation method and device and the image segmentation method and device applied to the slag pieces, the image can be segmented precisely

Segmentation method and device for disease speckles on edge-blurred leaves of protected-cultivation vegetables

Abstract: The present invention provides a segmentation method and a device for disease speckles on the edge-blurred leaves of protected-cultivation vegetables. The method comprises the steps of acquiring the gray value of any target point and the gray value of any adjacent point of the target point in a to-be-processed image; according to the gray values of all adjacent points of any target point, obtaining an average gray value of the neighborhood of the target point; according to k and the transverse and longitudinal coordinate offsets of any adjacent point of any target point, obtaining the weight value of any adjacent point of the target point; according to the gray value of all adjacent points of any target point and the above weight value, obtaining the weighted grayscale mid-value of the neighborhood of the target point; according to the obtained three values of the target point, establishing a three-dimensional histogram (hereinafter referred to as the histogram) and figuring out the region of any target point in the three-dimensional coordinate system (hereinafter referred to as a coordinate system) of the histogram; correcting the three values of the target pint according to a preset strategy; calculating the distance between any target point and the origin of the coordinate system according to the corrected values and conducting the dimension reduction of the histogram according to the distance; segmenting the histogram to obtain an optimal threshold based on OTSU; and segmenting the to-be-processed image according to the threshold. According to the technical scheme of the invention, the computer-aided segmentation for disease speckles is realized.

Technology for measuring mineral particle size based on multi-element multi-scale entropy

Abstract: The invention discloses a technical method for measuring a mineral particle size based on multi-element multi-scale entropy. The method comprises the following steps: firstly, respectively utilizing a sobel operator to enhance boundary, for three color variables R, G and B of coarse crushing, intermediate crushing and fine crushing mineral images; averaging each row of gradient data of ternary color variable of each level image; continuously intercepting an average row sequence of each color variable in fixed length according to the sequence; respectively averaging the data in each particle size data set of the ternary color variable; constructing a (n-m) set ternary compound delaying vector at the scale E and calculating a multivariate sample entropy, thereby acquiring multiple multi-scale entropy at 20 scales; lastly, establishing an associated model of the entropy and the mineral particle size utilizing the calculated multivariate sample entropy value of each-level mineral image gradient data, thereby detecting the mineral particle size under each-level crusher.