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128results about How to "Protection edge" patented technology

Eyeglass frame with integral channel to receive decorative inserts

A decorative eyeglass having a pair of temple frames adapted to receive an interchangeable temple insert with a decorative insert attached thereon. A flanged channel disposed in the temple bar of the temple frame is adapted to receive the temple insert through an end opening disposed in the proximal end of the temple frame. The temple insert includes a perimeter ridge rising above a central recessed surface adapted to receive the decorative insert and a flat temple end protecting the edges of the decorative insert from fraying and wear. The perimeter flanges of the temple insert prevent the temple insert from entering or exiting the channel via the side opening. Insertion and removal of the temple insert is accomplished by rotating the temple frame relative to the lens frame so as to expose the end opening. With the desired temple insert fully inserted into the channel, the temple frame may be rotated so as to block the end opening by the lens frame. A coordinated apparel system includes the eyeglass frame with a selected temple insert and decorative insert selected from a plurality of temple inserts each having a decorative insert displaying an ornamental feature wherein the decorative insert is selected such that the ornamental features of the decorative insert are matched and coordinated with the ornamental feature of a item of decorative apparel.
Owner:TABER JOHN A JACK

Adaptive compressed sensing-based non-local reconstruction method for natural image

The invention discloses an adaptive compressed sensing-based non-local reconstruction method for a natural image. The problems of serious reconstructed image information loss and the like in the prior art are mainly solved. The method is implemented by the steps of: (1) dividing an image into N 32*32 sub-blocks, obtaining a basic sensing matrix Phi' according to a basic sampling rate b and a sensing matrix Phi, and sampling a signal by utilizing Phi' to obtain a basic observation vector; (2) estimating a standard deviation sequence {d1, d2, ..., and dN} of the image according to the basic observation vector; (3) adaptively allocating a sampling rate ai for each sub-block according to the standard deviation sequence {d1, d2, ..., and dN}, and constructing an adaptive sensing matrix, and sampling the signal by utilizing the adaptive sensing matrix to obtain an adaptive observation vector; (4) forming an observation vector of each sub-block by using the basic observation vector and the adaptive observation vector; (5) obtaining an initial solution x0 of the image according to the observation vector; and (6) performing iteration by using x0, and reconstructing the original image until consistency with a finishing condition is achieved to obtain a reconstructed image x'. The method has the advantages of high image reconstruction quality, clear principle and operational simplicity, and is applied to the sampling and reconstruction of the natural image.
Owner:XIDIAN UNIV

Gas infrared image enhancing method based on anisotropic diffusion

The invention relates to a gas infrared image enhancing method based on anisotropic diffusion and belongs to the field of gas detection. The method comprises the following steps of: firstly, preprocessing a gas infrared video sequence image, and respectively processing by two ways, wherein one way uses a forward anisotropic diffusion algorithm so as to spread a gas cloud cluster region, and the other way uses a bidirectional anisotropic diffusion algorithm so as to reduce the noise, and protect and enhance the detail and edge of an image background; then, carrying out discontinuous frame difference on a first processing result, and accumulating difference results; and marking the gas cloud cluster region by the means that a K mean value is clustered in the accumulated result, confirming the position coordinate of the gas cloud cluster, and finally rendering the gas cloud cluster in a colorizing way according to the corresponding position of the coordinate in a second processing result, so that the interpretation property of the gas cloud cluster can be observably improved, the quality of the gas infrared image can be improved, and human eyes can quickly detect the formed gas cloud cluster when the gas leaks. The method can be used for detecting the leakage of the invisible hazardous gas.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY

Compressive sensing method based on principal component analysis

The invention discloses a compressive sensing method based on principal component analysis and mainly solves the problem of low sampling efficiency in the prior art. The method comprises the following steps of: (1) taking z images from a gray natural image library, taking a 32*32 sub-block from each image which is taken at intervals of three pixels along the horizontal and vertical directions to form a training sample set x1, x2, ..., and xm, and training a full-rank observation matrix Phi(f) for the training sample set x1, x2, ..., and xm by using a principal component analysis method, wherein z is not less than 15 and not more than 25, and m is the quantity of training samples; (2) dividing an image which is required to be sampled into n 32*32 sub-blocks x1, x2, ..., and xn, acquiring an observation matrix Phi according to sampling rate s and the full-rank observation matrix Phi(f), sampling each image sub-block by using the observation matrix Phi, and thus obtaining an observation vector y; (3) acquiring an initial solution x0 of the image according to the observation vector y; and (4) iterating according to the initial solution x0 until iteration is in accordance with end conditions, and thus obtaining a reconstructed image x'. The compressive sensing method has the advantages of high sampling efficiency, high image reconstruction quality and clear principle, and is easy to operate and applicable to sampling and reconstruction of a natural image.
Owner:XIDIAN UNIV

Automatic grain boundary extraction method for steel grain

InactiveCN106023134ASimple algorithmAlgorithm calculation speed is fastImage enhancementImage analysisCrystalliteImaging Feature
The invention discloses an automatic grain boundary extraction method for a steel grain. The method comprises the steps that 1 grain image preprocessing, wherein gray scale conversion, median filter denoising and binarization processing are carried out; 2 grain feature point extraction and feature distance calculation are carried out, wherein distance transforming, scale space generating, Gaussian difference scale space constructing, scale space feature point seeking and feature distance calculating are carried out; and 3 automatic grain boundary extraction is carried out, wherein initial contour drawing, grain boundary level set evolution extracting and final grain boundary determining are carried out. The results are as follows: (1) the distance between the two layers is calculated; Grain boundaries. A sift algorithm is used to acquire an image feature point after distance transformation and calculate the corresponding feature distance, and the initial contour is constructed to improve the evolution efficiency and precision of a level set algorithm. The requirements of high precision grain boundary extraction and grain measurement are effectively met. The defects of low precision and poor effect of grain boundary extraction and grain measurement in the prior art are overcome. The method is easy to understand and has the advantages of high applicability and high accuracy.
Owner:JIANGSU UNIV
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