74results about How to "Outstanding details" patented technology

The invention provides a commodity three-dimensional reconstruction system and a reconstruction method, wherein, the method comprises the following steps: S1, obtaining at least three point cloud images of commodities from different angles of view; S2, based on SAC-IA-ICP algorithm registers the point cloud of two adjacent point cloud images in order to eliminate the deviation between adjacent point cloud images. S3, adopting the improved Poisson surface reconstruction algorithm to reconstruct the complete three-dimensional surface model of the merchandise for all the point clouds after registration; S4, color rendering and illumination rendering are carried out on the commodity three-dimensional curved surface model by using an illumination renderer to obtain a three-dimensional commoditymodel that can be displayed. The three-dimensional commodity model constructed in the above method is more prominent in detail and more obvious in geometrical features. The effect is more real and the global shape and detail features of the commodity are truly restored.

The invention relates to an algorithm for fusing a multi-focusing image based on salient region extraction. The algorithm comprises the steps of 1, performing GBVS algorithm to obtain salient images of two source images; 2, performing binaryzation for the salient images, and respectively calculating the space frequency so as to obtain space frequency maps; 3, detecting the weak side edges of the space frequency maps by the watershed algorithm to obtain closed areas, classifying, comparing the space frequency of different regions to find out the false focusing areas, filtering the false focusing areas, and processing the rest regions by the morphological method to obtain a focusing area; 4, directly fusing the source image focusing regions, performing Shearlet conversion for the out-of-focus regions, and decomposing to obtain high frequency and low frequency sub-band coefficients, and respectively performing conversion and fusion based on PCNN and laplacian pyramid; 5, reconstructing the fusion coefficients to obtain a fusion image. With the adoption of the algorithm, the gray levels are dispersedly distributed, the image textures are rich, and the details are salient.

The invention discloses a face image-picture generating method based on sparse representation, which mainly solves the problems of low definition and blurry details of a pseudo image and a pseudo picture generated in the traditional method. The face image-picture generating method comprises the following implementation processes of: generating an initial pseudo image and an initial pseudo picture by using the traditional pseudo image and pseudo picture generating method; blocking all images and then training an image block dictionary and a picture block dictionary by utilizing a training sample set; synthesizing high definition characteristics information according to an input test picture block or an input test image block by utilizing the two dictionaries; adding the obtained high definition characteristics information and the corresponding initial pseudo image block or the initial pseudo picture block to obtain a final pseudo image block or a pseudo picture block with high definition; and fusing all pseudo images and pseudo pictures with high definition to obtain a complete pseudo image or a complete pseudo picture. Compared with the prior art, the generated pseudo image and pseudo picture have the advantages of high definition and obvious details and can be used for face identification and face retrieval.

The invention provides an angiography image blood vessel segmentation method and an angiography image blood vessel segmentation system. The angiography image blood vessel segmentation method includesthe steps of taking each pixel coordinate of a live image as a reference coordinate, selecting one pixel coordinate matched with the reference coordinate from a mask image and taking the pixel coordinate as a contrast coordinate; extracting sub images in the same size from the live image and the mask image respectively to form an image pair; inputting all the images to a dual-passage convolutionalneural network to output a first blood vessel segmentation image; extracting multiple images in different size from each reference image according to preset rules, inputting all the images in different size to a multi-scale convolutional neural network to output a second blood vessel segmentation image, and finally displaying the second blood vessel segmentation image. As the dual-passage convolutional neural network and the multi-scale convolutional neural network are utilized for achieving twice classification, blood vessels of the images displayed finally have defined boundaries and cleardetails, and during the whole process, full-automatic interaction is achieved with high efficiency.

The invention discloses a dental prosthesis stent made of metal additives and a method for manufacturing the dental prosthesis stent made of the metal additives. The method includes: acquiring data of a three-dimensional maxillary model of a patient, selecting a maxillofacial surface of the dental prosthesis stent on the model, reconstructing the maxillofacial surface, stretching the maxillofacial surface until formation of an initial stent model, and repairing the initial stent model to meet design requirements for forming a stent CAD (computer aided design) model available for printing and manufacturing; adopting a selective laser melting 3D (three-dimensional) printer for printing and manufacturing to obtain a stent model, and subjecting the stent model to thermal treatment and surface treatment. The dental prosthesis stent comprises a body made of a metal material, and the body comprises a nesting portion and a supporting portion with a mesh structure. The dental prosthesis stent made of the metal additives and the method for manufacturing the dental prosthesis stent made of the metal additives have the advantages that the structure meeting clinical requirements is made by means of 3D printing technology, high precision, high surface quality and short manufacturing period are realized, and the clinical requirements are met better.

The grey treating method for color plasma display screen includes dividing grey level into lower, middle and high grey levels; detecting image information with FPGA in statistic digital image algorithm and grey detecting module, judging the grey characteristic of the current image information with the image processing device, real-time regulating image through expanding one weighting 0.5 sub-field to form 9-bit binary number and to raise the grey output levels in lower grey range of 0-50 to 10, and correcting error generated during processing with the error corrector. The present invention adopts dynamic grey correcting method, can regulate the grey display correction curve automatically based on the real-time image grey and brightness so as to raise grey level, and has lest list checking error and raised image quality.

The invention discloses a method for eliminating cloud and haze of an atmospheric degraded image. The method comprises the steps of the acquisition of a dark channel image and mid-value filtering, the self-adaptive degradation and acquisition of an atmospheric light image, the detailing of an atmospheric transmission function and the visual correction of a color domain. The atmospheric degraded image to be processed by the method has the problems of different illumination intensities, contrast ratios and dynamic ranges, a dark channel theory model is adopted, and the mid-value filtering of the dark channel image, the self-adaptive degradation and acquisition of the atmospheric light image and the visual correction of the color domain are also combined to eliminate the cloud and haze, and the disadvantages in the prior art are overcome. Besides, the method for eliminating the cloud and haze of the atmospheric degraded image is simple to operate and has good application prospect.

The invention discloses a primary skin color keeping vein development method. The primary skin color keeping vein development method comprises the steps of acquiring a near infrared image and a visible light image at a position to be detected; matching the near infrared image with the visible light image; performing histogram most value mapping on the near infrared image and obtaining a near infrared output image corresponding to a visible light image luminance component extreme value; adopting a principal component analysis method to separate the visible light image, then performing residual error strengthening on a separated color component and finally performing principal component analysis inverse transformation on the visible light image subjected to the residual error strengthening; performing bilateral filtering on the near infrared output image and merging the image obtained after bilateral filtering with the near infrared output image Z to obtain a merged color imaged. By means of the primary skin color keeping vein development method, the problem that a traditional vein display image is unreal is solved, the merged color image can be ensured to be accurate in vein distribution and obvious in details, and the primary skin color in a non-vein region can be kept. The primary skin color keeping vein development method can widely applied to the field of medical image processing.

The invention discloses a train precise positioning method and system based on rail geometrical characteristic information matching. The method comprises the following steps of S1, performing time synchronization on the positioning data and the rail geometrical state parameters; S2, performing inertial navigation resolving according to IMU data; S3, performing melt resolving on the inertial navigation result and the rail mileage data; reckoning the mileage reckoning value; S4, on the basis of the time relevance, giving the mileage reckoning value to the rail geometrical state parameters to obtain a rail geometrical state parameter sequence; S5, performing matching on the rail geometrical state parameter sequence and the preset mileage related rail geometrical state parameter sequence to obtain a matched mileage value; S6, performing combined processing on the mileage reckoning value and the matched mileage value to obtain the optimum mileage estimation value. The rail geometrical state parameter is used as the characteristic signal; the characteristic signal and the preset mileage related rail geometrical state parameter sequence are subjected to relevance matching, so that the decimeter grade or even centimeter grade train positioning precision can be realized.

The invention discloses a multi-threshold-value segmentation method based on a gray level histogram. According to the multi-threshold-value segmentation method, the maximum between-cluster variance principle is used, a dichotomy serves as the basis, and a minimal-value point in the gray level histogram serves as a reference point of multi-threshold-value segmentation. The multi-threshold-value segmentation method includes the steps of firstly, finding out a first threshold value of the gray level histogram according to the otsu method, secondly, respectively solving to obtain the maximum between-cluster variances of the two parts of the segmented histogram based on the dichotomy, thirdly, comparing the two variances, and finding out a threshold value corresponding the maximum variance to serve as a threshold-value point of next-time segmentation, fourthly, executing the three steps repeatedly until the given number of the threshold values is achieved, fifthly, finding out all wave trough points according to the smoothed histogram, and finally, comparing all the obtained threshold values with the wave trough points, and finding out the wave trough point closest to the threshold values to serve as the final threshold value. Compared with a traditional multi-threshold-value segmentation method, the multi-threshold-value segmentation method has the advantages that a part of segmentation noise is eliminated, and the segmentation effect and the adaptability are better than existing algorithms.

The invention discloses a new image fusion method based on shift invariance shearlet transformation (SIST). The method includes the implementation steps of firstly, conducting multi-scale multi-direction decomposition on a source image through SIST to obtain low-frequency sub-band coefficients and high-frequency sub-band coefficients; secondly, reflecting the outline information of the image through low-frequency sub-bands, obtaining local structure descriptors for identifying the image resolution through a local structure tensor singular value decomposition method, making the local structure descriptors serve as movement measure functions in the fusion strategy, and adopting large strategy fusion. High-frequency sub-bands display detail information of the image. The invention provides a new edge strength measurement method, and a multi-strategy fusion rule based on the sigmoid function and edge strength measurement is made and used for high-frequency sub-band fusion. Finally, reverse SIST is conducted on the obtained fusion coefficients to obtain a final fusion image. The method overcomes the defect that edge distortion is easily caused by a traditional image fusion method, and more edge and detail information is reserved through the fused image.

An embodiment of the invention discloses a thermal imaging image processing method and device. The method comprises the following steps: determining a view field overlap area of a thermal imaging image and a visible light image; determining hue value of each pixel point in the view field overlap area according to temperature quantized value of each pixel point in the view field overlap area in the corresponding pixel point in the thermal imaging image; determining brightness value of each pixel point in the view field overlap area according to the brightness of each pixel point in the view field overlap area in the corresponding pixel point in the visible light image; determining saturability value of each pixel point in the view field overlap area according to the temperature quantized value of each pixel point in the view field overlap area in the corresponding pixel point in the thermal imaging image and / or saturability in the corresponding pixel point in the visible light image; and generating a color image of the view field overlap area according to the hue value, brightness value and saturability value of each pixel point in the view field overlap area. The scheme can distinguish details of a target, and improves identification degree of the target.

The invention discloses a method for dynamically calibrating image light intensity on the basis of environmental factors. The method includes the steps of reversing an image to distinctly display key areas; segmenting the image into NxN sub-blocks for processing; processing the sub-blocks via power transformation; processing the sub-blocks via grayscale mapping transformation; subjecting the sub-blocks to histogram processing; processing the sub-blocks via dynamic fuzzy histogram equalization; respectively processing the sub-blocks via masking and filtering by a hybrid space processing method; iterating every sub-blocks of the NxN sub-blocks by a Lucy_Richardson filter; respectively calculating to optimize the power transformation step and the dynamic fuzzy histogram equalization step of the sub-blocks by a fuzzy logic theory; and reversing the image again and outputting the final image, wherein the N is an integer nine, the maximum information entropy is judged as the optimum optimizing standard. By the aid of the method, information entropy of the image is effectively increased, and good light calibrating effect is obtained.

The invention discloses an inconsistent image blind restoration method based on sparse representation. The method comprises steps of: creating an inconsistent image fuzzy degeneration model depending on a camera three-dimensional shaking model in combination with over-complete dictionary representation of a natural image; inputting a fuzzy image to be restored and an over-complete dictionary to solve an initial sparse coefficient and initializing a parameter; using the over-complete dictionary representation of the natural image sparsity of the fuzzy core and sparse coefficient as the regular constraint of the model, and transforming the resolution of the inconsistent blind image restoration model into multiple simple subproblems by using an alternate iteration method so as to achieve blind restoration of the fuzzy image y. The method has better restoration effect on the fuzzy image acquired on natural condition, achieves restored images with clear details, no distortion, and low noise, has better visual effects and extendibility.

The invention discloses an area energy photon counting image fusion algorithm based on an adaptive threshold value, and belongs to the technical field of image fusion. The method is characterized by comprising the following steps of step 1001, carrying out redundant wavelet transformation; step 1002, calculating regional energy, neighborhood mean square error, matching degree and self-adaptive threshold value; step 1003, calculating a weighting coefficient and an enhancement factor; step 1004, calculating a matching degree; step 1005, judging a matching degree and a self-adaptive threshold value; step 1006, when the matching degree is smaller than a self-adaptive threshold value, selecting an enhancement value of a pixel point of an area with high energy as a corresponding pixel point value in the fusion image; step 1007, if the matching degree is greater than or equal to a self-adaptive threshold value, adopting a weighted area energy method; and step 1008, obtaining a photon countingfusion image. Through the algorithm, the problems of unclear contour, serious noise, photon counting image information redundancy under extremely weak illumination, unclear details and the like of afusion image obtained through a regional energy fusion method are solved.

The invention relates to a digitized virtual hand anatomy construction method, which includes the following steps: A, specimen selection and pretreatment; B, specimen injection; C, CT scanning for data set acquisition; D, visualized three-dimensional reconstruction of the hand on a common PC platform through Mimics software developed by Belgian Materalise company, which includes the steps of a, three-dimensional reconstruction of the outline of the hand; b three-dimensional reconstruction of bones; c, three-dimensional reconstruction of the artery of the hand; d, three-dimensional reconstruction of the tendons of the hand. The construction method for the first time realizes comprehensive digitized three-dimensional reconstruction of a hand anatomy and converts two-dimensional pictures commonly used in clinics into three-dimensional pictures, which is good for further improvement of understanding of human hand and provides scientific basis for clinical diagnosis, treatment program formulation and related operations.

The invention discloses an electrolytic corrosion method of high strength and high toughness Fe-Mn-C series twinning induced plasticity (TWIP) steel. The steel is the second generation of the TWIP steel and is suitably used in the car impact resistant structural component and in other fields. The steel contains the following chemical components by weight percent: 0.2-0.7% of C, 17-24% of Mn and the balance Fe and inevitable impurities generated by the smelting process. The electrolytic corrosion method is characterized in that the electrolytic corrosion liquid is the mixed solution of 10% of perchloric acid, 80%-90% of glacial acetic acid and 0-10% of glycerol by volume, the working voltage is 30-45V; the current density is 0.5-1.5A / cm<2>, the corrosion time is 30-120s, the temperature of the corrosion liquid is 10-50 DEG C and the distance between the cathode and the anode is 1-5cm. The method of the invention is simple and practical and has good repeatability; the surface of the prepared TWIP steel does not have scratches and the surface deformations caused by polishing deformation such as the disturbing layer and the deformation twin, and the TWIP steel of the invention can satisfy the experimental requirements of the metallurgical phase, the type analysis of grain boundary, the strain test and the texture measurement on different sizes of Fe-Mn-C series TWIP steel samples.

According to the underwater image restoration algorithm based on the color line model, the color line model in the atmosphere can be substituted into the underwater image generation model and the fogimage formation model on the premise that the low operation complexity is kept, and the problem that the definition contrast ratio of an underwater original shot image is not high and the color difference is obvious is solved. Experimental results show that the underwater image restoration task can be well achieved through the algorithm, a reconstructed clear image is closer to a real scene, the color is accurate, details are obvious, and better subjective performance and objective quality are achieved.

The invention provides a monitoring device with an HDR display function. The monitoring device comprises a display screen, as well as an input module used for receiving Video, VGA, DVI, HDMI, SDI and other monitoring image signals input by a front end; an image conversion module used for converting the received monitoring image signals into a RGB mode to conveniently process an image; and HDR processing module used for mapping image RGB data; and a display module used for sending the processed image signals to the display screen to be displayed. The monitoring device provided by the invention has the following advantages: 1. the HDR image input by the front end is mapped, so an image with obvious details, clear color levels and a high dynamic range effect is displayed in a monitoring display device with a limited dynamic range, and then the image is convenient to be monitored and identified. 2. the HDR processing function is realized by FPGA programmable logic, the programmability is high and the design is flexible. 3. the structure is simple, the cost is low and the use is convenient.

The invention discloses an image rapid defogging method and a device, a terminal and a storage medium, and the method comprises the steps: dividing an original foggy image into a sky region and a non-sky region through a sky region recognition algorithm; performing CLAHE enhancement on the sky region through a CLAHE enhancement algorithm to obtain a defogged image of the sky region; through an improved dark channel theory, firstly performing dark primary color enhancement and CLAHE enhancement on a non-sky area, then taking the mean value of the dark primary color enhancement and the CLAHE enhancement to enhance the contrast ratio and the brightness, and a defogged image of the non-sky area is obtained; and performing defogging restoration processing on the defogged image of the sky area and the defogged image of the non-sky area to obtain a defogged image corresponding to the original foggy image. According to the method, the problem of sky area failure in the prior art can be effectively avoided, the problems of sorting and cyclic traversal in the atmospheric light value calculation process are reduced, implementation of an algorithm on hardware is facilitated, and meanwhile theeffects of appropriate brightness, obvious details, overall image balance and color distortion prevention can be achieved.

The invention discloses a processing method for image detail presentation, a device and a vehicle. The method comprises steps that a gray image of a to-be processed image is acquired; histogram equalization of each row of pixels of the gray image is carried out to acquire a first image; histogram equalization of each column of pixels of the first image is carried out to acquire a second image; the second image is outputted to be a result image. According to the processing method for image detail presentation, the device and the vehicle, the histogram equalization method is optimized, the method is suitable for the field having relatively high image detail presentation requirements, so image details can be enhanced to the maximum degree, and the image after being processed has more obvious details.

The invention relates to a medical endoscope image enhancement method based on mathematical morphology, which realizes medical endoscope image enhancement based on HSI and morphological filtering, andcomprises the following specific steps: step 1, reading an original image, and converting a color space of the image into an HIS color space; step 2, keeping the hue H and saturation S of the image unchanged, and performing morphological filtering on the brightness I to realize brightness detail enhancement; and step 3, converting the processed image pixel value from the HIS color space to the RGB color space. According to the method, the brightness component of the color medical endoscope image can be properly enhanced, compared with the original image and the enhanced effect, the contour and details are more prominent, the image is clear, the color is bright, and introduction of excessive image noise is basically avoided.

An image processing method for obtaining a relief retro effect suitable for laser engraving obtains an effect image XT of an enhanced edge and an effect image VO of color and edge equalization respectively according to an original image P. Then multiplying the effect map XT by the effect map V0, the mixed effect map OS is obtained, and the mixed effect map OS is normalized to 0-255, to obtain thefinal relief retro effect drawing O. The method can be used to obtain a clear outline, hierarchical relief retro effect map. The relief retro effect picture obtained by the method of the invention canbe carved by an engraving machine to obtain the relief retro effect picture with clear image outline, space feeling, primary and secondary feeling, good sense of hierarchy, prominent detail and natural color transition.

The invention discloses a wide dynamic image enhancement method and apparatus. The method comprises the following steps of extracting a first grayscale value of each pixel of an original image; judging whether the first grayscale value of each pixel is less than a first average grayscale value or not, wherein the first average grayscale value is an average grayscale value of all pixels of the original image; if the first grayscale value is less than the first average grayscale value, performing first function transformation on the first grayscale value to obtain a second grayscale value, wherein the first function is an increasing function in a predetermined numerical value range and a convex function with a smooth curve; and displaying the image according to the second grayscale value. The grayscale expansion of a low-grayscale region of the original image is realized by utilizing a characteristic that the slope of the first function in the predetermined numerical value range is greater than 1, so that the contrast ratio of the low-grayscale region is increased and details are more remarkable.

The invention discloses an infrared image enhancement method based on weighted guided filtering, belongs to the technical field of image enhancement, and aims to solve the problems that the existing image detail processing enhancement is not obvious enough and the edge texture is not well improved.The method comprises: processing an input high dynamic range infrared image by means of an improved multi-scale weighted guided filtering, obtaining the two layers of detail layer images and one layer of base layer image; carrying out contrast-limited adaptive histogram equalization processing on the base layer image, stretching the contrast and compressing the dynamic range to obtain a base layer enhanced image; processing the two detail layer images obtained after processing in the step 1 by adopting a maximum posteriori method based on a Poisson-Markov random field, adding certain information, and then carrying out dynamic range compression based on gamma correction to obtain two detail layer enhanced images; and carrying out linear fusion on the obtained basic layer enhanced image and the detail layer enhanced image according to weights, and finally obtaining an enhanced image.

The invention relates to an image denoising processing system of an X-ray inspection instrument. The image denoising processing system of the X-ray inspection instrument comprises an image storage unit, an image processing unit and an image display control unit. The image storage unit adopts a high-definition image storage mode and saves images in a BMP format. The image processing unit mainly comprises histogram equalization and noise reduction by using a multiframe average filtering algorithm, the module of the image processing unit adopts an embedded control system and can read data signals of an image memory at any time, the noise signals in X-ray images can be effectively reduced through the programmed algorithm of the image processing unit, and image quality can be improved. The image display control unit carries out an encoding process and an electrical level transformation process on output parallel signals through an internal programmable array design, and enables the data signals to be capable of being displayed as clear images through a display part. The image denoising processing system of the X-ray inspection instrument is widely involved in application, and improves the image quality.

The invention relates to the technical field of face image processing, in particular to a shooting method as well as a device and electronic equipment thereof. The shooting method comprises the following steps: during taking a picture, receiving a focusing command, and enabling the focusing command to be used for determining the focusing position of a shot object in advance; collecting a pre-shooting image of the shot object; identifying the focusing position to which the focusing command points in the pre-shooting image; and focusing a pointed focusing position to shoot and save. Therefore, by accurately identifying the focusing position of the shot object and shooting, the shot object is more definite, and the detail of the shot object is highlighted more.

The invention discloses an automatic steel cord bulking detection device. The device comprises a motor, a bracket, a console and a high-definition camera; a guide rail is horizontally arranged on thebracket, a sliding bloke is arranged on the guide rail, an upper detachable rubber sheet and a lower detachable rubber sheet are arranged at a hollow part of the sliding block; the console comprises adisplay screen, a keyboard, a PLC controller and a storage unit; the console is electrically connected with the motor, the high-definition camera, a cord pretension setting point; the high-definitioncamera is located at one side, towards a head part of the bracket, of the sliding block; the console further comprises a card reader; an image identification module and an identity identification module are arranged on the PLC controller; the storage unit is used for storing standard steel cord, to-be-detected steel cord and personnel identity and like information. The invention further providesa use method of above detection device. The bulking condition at the full section of the steel cord can be detected by adopting a following shot way, the artificial visual detection is replaced by combining an image identification function, the efficiency is improved, the measurement range is large, and the precision is high; and the steel cord quality trace management by the inspection personnelis convenient.