810 results about "High contrast" patented technology

The invention relates to the technical field of machine vision and perception, in particular to a ton bag lifting unmanned control system based on a binocular vision camera and a laser radar, which comprises an intelligent control unit, a lifting appliance executing mechanism, a sensing unit and a special ton bag, the sensing unit comprises a binocular vision camera and a laser radar and is used for collecting depth vision and three-dimensional point cloud information of an operation area; the intelligent control unit fuses multi-source data, locates a lifting lug by improving a weighted multi-feature fusion algorithm, plans a safety path and generates a staged instruction; the lifting appliance executing mechanism lifts and pulls a collapsed lifting lug through an electromagnetic adsorption module, a mechanical gripper module clamps the lifting lug, and reliable operation is achieved in cooperation with a verification mechanism; the special ton bag is matched with a sensing and executing module through a high-contrast color and a pre-embedded metal piece. The full-process unmanned operation is achieved, the robustness and operation safety of the complex environment are improved, and the ton bag hoisting requirements of multiple industries are met.

The invention discloses a multispectral image fusion model based on a double-branch self-attention-generative adversarial network and a fusion method thereof, and the model sequentially comprises an input preprocessing module which is used for carrying out the same-amplitude mapping, normalization and overlapping block embedding of visible light and infrared original images, and generating a to-be-fused feature block; the double-branch encoder module captures a cross-modal long-distance dependence and overall brightness structure through multi-head deep convolution transpose attention (MDTA) and a gated deep convolution feedforward network (GDFN), and extracts high-frequency texture and edge information by using a reversible residual gating layer and detail DetailNode iteration; the fusion decoder module is used for carrying out multi-level self-attention-convolution reconstruction on the two paths of features after channel dimension splicing, and outputting a single-frame high-resolution fusion image; and the double-domain discriminator module comprises a visible light domain discriminator and an infrared domain discriminator which are respectively used for carrying out adversarial evaluation on the fused image and the corresponding modal truth value image so as to improve the detail authenticity and the thermal target contrast ratio of the fusion result. The technical problems that an existing infrared-visible light image fusion method is insufficient in detail reservation, unbalanced in brightness and contrast, poor in unsupervised training stability and the like are solved, the method can be deployed on embedded platforms needing real-time and multi-modal information enhancement such as night monitoring, unmanned driving and edge security and protection, and high-contrast and high-information-amount fusion imaging is achieved.

The invention provides a facial skin flaw enhancement method based on a Lab color space. The method comprises the following steps: firstly, acquiring an RGB face image and converting the RGB face image into a CIE Lab color space with uniform perception; then, performing differentiation treatment according to the manually selected skin flaw type: for the vascular flaw, extracting statistical characteristics of a component and driving adaptive nonlinear transformation, and generating a grey-scale map which highlights the red flaw; for pigment flaws, nonlinear transformation is carried out on the component L, and then collaborative linear weighting and feature amplification are carried out on the component L, the component a and the component b, so that a grey-scale map with highlighted pigment spots is generated. And finally, coloring the grey-scale map in the Lab color space through adjustable parameters to generate a high-contrast color enhanced image. The method overcomes the dependence on hardware and training data in the prior art, can clearly and adaptively enhance various flaws such as acnes, couperose streaks and color spots, shows robustness under different illumination, and can be widely applied to clinical beauty, later photography and real-time video processing.

A scan driving method for rendering a high-contrast image, for use in a cholesteric liquid-crystal display device, is provided. The cholesteric liquid-crystal display device includes a display panel and a driving circuit section. The method includes: utilizing the driving circuit section to sequentially activate each scanning electrode using a modified pulse-width modulation (PWM) scanning procedure including a first stage, a second stage, and a third stage in sequence; and utilizing the driving circuit section to apply one or more alternating-current (AC) voltage pulses to pixel circuits on a first scanning electrode during the first stage to manipulate grayscale values of the pixel circuits thereon to be written in the second stage. During the first stage of the first scanning electrode, the pixel circuits on the remaining scanning electrodes within the third stage sense a zero voltage during a high-voltage period within the first stage of the first scanning electrode.

The invention belongs to the technical field of deep learning and image processing, and discloses an underwater image enhancement method based on tensor learnable prior. By designing learnable prior based on a Tensor Train kernel, explicit modeling of the underwater degradation law is realized. The four Tensor Train kernels correspond to the height, the width, the channel and the image block modality respectively, so that the system can simultaneously describe the vertical structure change, the horizontal scattering, the spectral absorption difference and the regional scale attenuation, thereby obviously enhancing the description capability for the underwater multimode degradation. The Tensor Train kernel is dynamically generated based on the kernel prediction sub-network, the prior structure of the method can be adaptively adjusted along with the input image, and the stability and generalization ability of the enhancement result are improved. According to the method, color shift is effectively corrected and scattering blur is inhibited while the structure edge is kept, so that the enhancement process is changed from traditional black box type mapping to physical consistency structured reasoning, and more natural colors, higher contrast and better detail recovery effects are obtained in a complex turbid environment.

The invention relates to the technical field of machine vision detection, particularly discloses a mechanical part surface defect vision detection system, and aims to solve the problems of blind areas, environment light sensitivity, insufficient tiny defect detection capability and the like in the detection of complex curved surface high-reflection parts. Comprising an optical imaging module, a geometrical morphology sensing module, a dynamic polarization regulation and control module, an image fusion and enhancement module and a defect identification and decision module. The three-dimensional morphology of the surface of the part is sensed in real time, the imaging polarization state is dynamically regulated and controlled according to the three-dimensional morphology, multi-frame polarization image fusion and digital diffraction enhancement processing are combined, full-coverage and high-contrast detection of the complex curved surface part is achieved, motion blur is effectively restrained, and the detection capacity of sub-pixel-level tiny defects and the system environment adaptability are improved.

The invention relates to the technical field of computer vision, and discloses a Monte Carlo tree search-based camera lens assembly focusing calibration algorithm and system, and the algorithm comprises the steps: constructing a three-dimensional search space comprising a focus position, a horizontal inclination angle and a vertical inclination angle, and combining a high-contrast cross wire test pattern to generate a local definition matrix; calculating an initial inclination angle based on the matrix to construct a root node of the Monte Carlo tree; according to the algorithm, an optimal search path is dynamically selected by applying an upper confidence bound strategy, child nodes are expanded in a three-dimensional space, physical adjustment is executed, and optimal three-dimensional configuration parameters are finally determined based on node scores through back propagation iterative optimization. The method breaks through a traditional one-dimensional search framework, effectively avoids a pseudo peak trap caused by inclination of a lens-sensor axis, improves the calibration precision and efficiency of the full-view-field definition of the camera, and achieves the precise positioning of a global optimal solution under a complex assembly tolerance.

The invention discloses an SAR (Synthetic Aperture Radar) image MTF (Modulation Transfer Function) quality evaluation method and system based on a natural scene edge, and the method comprises the steps: building a selection standard system for automatic edge screening of a natural scene SAR image, and determining a high-contrast linear edge according to the standard system; automatically detecting a high-contrast linear edge in the natural scene, and intercepting a region of interest for subsequent calculation based on the position of the linear edge; gray level distribution is extracted in the normal direction of the linear edge, and an edge spread function is constructed and used for describing gray level transition response of the imaging system in the edge area; carrying out normalization and smoothing processing on the edge spread function, and carrying out spatial domain first-order differential calculation to obtain a line spread function; and performing fast Fourier transform on the line spread function to obtain a modulation degree transfer function curve, and representing the detail transfer capability of the system under different spatial frequencies. According to the method, the imaging quality of the SAR image of the natural scene can be automatically, accurately and quantitatively evaluated under the condition that manual field arrangement is not needed.

The invention discloses an automatic calibration method and system for a cutting knife needle, a cutting machine and a storage medium. The method comprises the steps that a cutting knife needle is controlled to execute a gradient retraction cutting sequence, and the extension length of the knife needle retracts by a preset gradient length after each time of cutting; collecting a trace image formed on the calibration material by cutting each time through a camera; automatically identifying the shallowest effective cutting trace in the sequence based on image analysis; and calculating the reference zero point of the tool nose according to the sequence number corresponding to the trace, the preset gradient length and the initial extension length. The calibration material has a high-contrast substrate layer and contrast layer structure. The invention further discloses a system for implementing the method, the cutting machine comprising corresponding hardware and a storage medium. According to the invention, full automation of the calibration process is realized, dependence on artificial experience is eliminated, and the method has the advantages of high calibration precision, high efficiency, good consistency and the like.

The invention discloses an industrial visual inspection method based on edge light scanning, which comprises the following steps of: initializing projector parameter setting, adjusting shooting frequency and exposure time of an industrial camera, acquiring defect images and forming an image sequence according to the size and the material of a detected piece and an expected defect type to be detected and based on an edge light scanning method; carrying out fusion operation on the image sequence, enhancing defect signals of the images through a weighted stacking algorithm by utilizing high-contrast characteristics of defect areas in multiple frames of images, and carrying out defect positioning and classification on the enhanced images by adopting an image segmentation technology, so as to realize visual detection on defects of the detected piece; by optimizing the design of an optical imaging system, edge light scanning of the quartz wafer is realized, defects are highlighted, surface defects can be quickly and accurately identified, the detection efficiency is greatly improved, defect characteristics are directly enhanced in an image acquisition stage, and quick and accurate defect detection is realized in combination with a sequence image analysis technology.

The invention discloses a variable view field Linnik interference microscopic system and a measurement method thereof, and belongs to the field of laser measurement instruments, and a variable diaphragm is introduced into a reference arm of an interference system to realize matching of objective lenses of different test arms, so that light field spatial correlation under speckle illumination is maintained; meanwhile, a light source system with a delay line structure is adopted to accurately compensate the optical path difference introduced by the asymmetric objective lens configuration, so that the acquisition of a high-contrast interference pattern is realized. The method can effectively improve the quality of an interference image, has a depth selection function, and is suitable for dynamic phase imaging in different view field ranges. The technical scheme of the invention shows good imaging effect and adaptability in the aspects of dynamic imaging and depth layering.

The invention relates to the field of industrial visual inspection, and discloses an ultraviolet visible light confocal object image double telecentric imaging optical system which comprises a first lens, a second lens, a first gluing piece, a diaphragm, a second gluing piece, a third lens and a fourth lens which are sequentially arranged from an object plane to an image plane, and an optical axis serves as a rotation center. Wherein the object surface of the first lens is a convex spherical surface, the curvature radius of the first lens is 110.02 mm, the image surface of the first lens is a concave spherical surface, and the curvature radius of the first lens is 65.59 mm; the object surface of the second lens is a concave spherical surface, the curvature radius of the second lens is-200.11 mm, the image surface of the second lens is a convex spherical surface, and the curvature radius of the second lens is-130.80 mm. The system can be suitable for measuring an object with the object distance of 110 mm and an industrial camera with the imaging image surface diameter of 11 mm or below, the aperture of the system is F / 8, the system is also suitable for ultraviolet and visible light environments, it is ensured that lossless and high-contrast imaging can still be achieved in different light source environments, and therefore high-precision and high-reliability surface defect recognition and classification tasks are supported.

The invention relates to the technical field of projection modules, and particularly discloses an LCOS laser projection module, which comprises a laser light source module, a laser speckle eliminator, a reflector, a diffuser, a collimating lens, a fly-eye lens, a relay lens, a first linear polarizer, a polarizing beam splitter, an LCOS chip, a second linear polarizer and a projection lens which are sequentially arranged along a light transmission path, the laser light source module is provided with a light source optical axis and is used for emitting light, and the light is projected by the projection lens after being modulated along a light transmission path to form a projection image. The light emitted by the laser light source has the advantages of narrow divergence angle, small light-emitting area and good light concentration and collimation, the resolution of a projected image can be improved, the projected image is bright in color and high in definition, and the requirements of simple structure and small size are met. Meanwhile, the laser speckle can be eliminated through the matching of the laser speckle eliminator and the diffusion sheet, and the projection image can meet the high contrast through the existence of the first linear polarizer and the second linear polarizer.

The invention relates to the technical field of optical elements, in particular to a structural color regulation and control device based on silicon nitride metasurface continuous domain bound state enhancement, which comprises a substrate and a metasurface structure arranged on the substrate, the substrate is a silicon dioxide substrate, and the metasurface structure is composed of a plurality of nano-disks which are periodically arranged in a two-dimensional manner. And a circular air hole is formed in the nano plate. Based on the narrow linewidth resonance characteristic of the quasi-BIC, the structural color with high saturation and wide color gamut is realized; by utilizing strong polarization dependence, passive and dynamic regulation and control of color brightness can be realized through simple polarization rotation, and the structure does not need to be changed; silicon nitride has extremely low loss in a visible light band, good compatibility with a silicon dioxide substrate and a stable structure; a high-contrast polarization encryption pattern is easy to realize, and the application prospect in the fields of high-end anti-counterfeiting, information storage, dynamic display and the like is wide; the adopted micro-nano processing technology is standard and mature, and practical preparation and industrialization of the device are facilitated.

The invention relates to the technical field of engine cylinder body and cylinder cover surface defect detection, and discloses a visual detection method for engine cylinder body and cylinder cover surface defects, which comprises the following steps of: acquiring engine cylinder body and cylinder cover surface images under various different imaging conditions, preprocessing, extracting a feature vector of each pixel block, distributing weights by using a weight function, and calculating the surface defects of the engine cylinder body and cylinder cover. The method comprises the following steps: extracting a suspected defect area, introducing a loss function for verification, constructing a causal graph, calculating the probability of each defect type through causal inference, providing a decision basis for final output decision, and finally outputting a defect result. By integrating multi-angle illumination, multi-spectral imaging and laser scanning systems, rich information of the surface under different physical characteristics can be obtained, and it is ensured that various types of defects can present high contrast characteristics under at least one imaging mode.

Glasses are disclosed which can be used to produce substrates for flat panel display devices. The glasses may be substantially alkali free. The glasses are doped with one or more transition metals (e.g., Ni, Co) and exhibit reduced optical transmittance to suppress light leakage from the display device and / or to improve contrast. The display device may be a bottom emission display device or a top emission display device. The display device may be a tiled display device. Glasses disclosed herein may be used, for example, as a baseplate having a plurality of display substrates disposed thereon, a display substrate (e.g., backplane) having a plurality of light emitters disposed thereon, a glass cover plate, or combinations thereof.

The invention relates to the technical field of radiotherapy, and discloses a mold body for radiotherapy image deformation registration verification and a verification method.The mold body comprises a base, a water mold is placed at the top of the base, an observation assembly is installed at the top of the base, a deformation assembly is installed in the water mold, and an extrusion assembly is installed in the base; a rotating assembly is installed at the bottom of the base, the deformation assembly comprises a supporting column, the supporting column is fixedly connected to the interior of the water mold, connecting pieces are fixedly connected to the sides, opposite to the supporting column, of the water mold, deformation blocks are fixedly connected to one ends of the multiple adjacent connecting pieces, and the deformation blocks are fixedly connected to the other ends of the multiple adjacent connecting pieces. A plurality of second metal beads are fixedly connected to the outer surface of the water mold. High-contrast metal mark points are arranged inside and outside the die body, the actual space positions before and after deformation of the die body are accurately obtained by using an image processing technology, and a physical true value independent of a software algorithm is provided.

The invention discloses a preparation method of a silicon dioxide-epoxy resin composite material, the acoustic impedance of the composite material is controlled by adjusting the volume fraction of the silicon dioxide-epoxy resin composite material, an ultrasonic transducer prepared by utilizing the composite material and a preparation process thereof, and an imaging system designed by utilizing the ultrasonic transducer. By designing the matching layer and the backing layer with specific acoustic impedance, seamless fusion of ultrasonic imaging and photoacoustic imaging is realized, the transducer has ultrahigh sensitivity, broadband characteristic and high optical transparency, shows bimodal imaging capability of high contrast and high resolution, and solves the problem that a traditional transparent ultrasonic transducer is insufficient in acoustic performance.

The invention discloses a feed raw material impurity online detection and grading method based on multispectral fusion, and the method comprises the steps: deploying a multispectral imaging device above a raw material conveying device, and synchronously collecting a visible light wave band image and a near-infrared wave band image of a flowing feed raw material; the near-infrared band image comprises organic matter molecular bond vibration absorption characteristic information; performing space-time alignment on the acquired visible light band image and the near-infrared band image through an image registration unit to generate space-time matched dual-channel image data; and constructing a multispectral fusion model, inputting the two-channel image data into the fusion model, and fusing visible light band texture information and near-infrared band organic matter absorption features through a weighted feature superposition algorithm to generate a high-contrast fusion image. According to the method, the accuracy and grading reliability of online impurity detection of the feed raw materials are remarkably improved, and the two core problems that dynamic registration is not accurate and foreign matter characteristics are shielded by particle stacking are effectively solved.

The invention belongs to the technical field of condition judgment, and particularly relates to an electrode foil corrosion condition judgment method and system, and the method comprises the following steps: S1, obtaining a grayscale image of a to-be-analyzed electrode foil; constructing a structure tensor based on the composite gradient reflecting the local brightness and texture information of the pixel points, determining an anisotropic diffusion coefficient according to the structure tensor, and performing iterative anisotropic diffusion filtering processing on the grayscale image by using the anisotropic diffusion coefficient to obtain a filtered image; and S2, fusing the anisotropic diffusion coefficient determined for each pixel point with the pixel intensity of the filtered image to obtain a high-contrast corrosion significance map. According to the method, the contour edge information of the corrosion area can be kept while the complex texture and noise of the background area of the electrode foil image are smoothed, the contradiction between denoising and edge protection of a traditional filtering method is solved, the result of the corrosion condition is more reliable, and the automation level of electrode foil product quality detection is improved.

The invention discloses a radiotherapy image reconstruction method based on self-supervised learning. The method comprises the following steps: S1, obtaining a low-contrast radiotherapy image sequence data set; s2, constructing the low-contrast radiotherapy image sequence data set into a key-query pair according to view angle difference, inputting the key-query pair into a MoCov3 self-supervision feature encoder model, and obtaining an initial feature representation set; s3, obtaining an image enhancement reconstruction result set; s4, generating an updated wolf pack parameter set; s5, outputting the optimal reconstruction parameter configuration and the corresponding high-contrast radiotherapy enhanced image; and S6, inputting the high-contrast radiotherapy enhanced image into a closed-loop quality evaluation module, and performing final quality verification by using an organ sketching consistency index and a dose recalculation error. According to the invention, the response capability of the encoder to the tumor boundary is obviously improved.

The invention provides a multi-mode visual touch fusion sensor of a non-coaxial light path, which realizes multi-mode cooperation of a visual mode and a visual touch mode by performing non-coaxial arrangement on the optical axis of a camera and the central normal of a touch plane on a structural level; a virtual binocular system is constructed under the condition of a single camera by means of a free-form surface light splitting biprism, the number of devices and the assembling freedom degree are reduced, and therefore the integration degree and calibration consistency are improved; a semi-transparent and semi-reflective optical element is matched with an LED light-emitting unit time sequence and a control circuit to realize automatic and rapid mode switching, so that the long-term reliability is improved, and the switching service life is prolonged; through the collaborative design of the self-assembled metal nano reflective coating and the thin polyurethane packaging layer, a high-contrast and wear-resistant deformation image is obtained on the premise of not sacrificing the tactile sensitivity, and finally continuous acquisition of a target pose and contact parameters is realized. And the comprehensive requirements of accurate grabbing and touch closed-loop control on stable imaging, rapid switching, easy integration and high reliability are met.

The invention discloses a multi-angle polarization imaging method and system for micro scratches on the surface of an aluminum plate, and the method can convert the physical difference which cannot be distinguished by naked eyes and a common camera into a significant gray difference on an image through calculating a Stokes parameter and constructing a polarization feature image, thereby forming a high-contrast detection image, and improving the detection precision. The detection sensitivity and the signal-to-noise ratio are obviously improved; the method is extremely sensitive to polarization state disturbance caused by changes of the surface microstructure of the aluminum plate, interference of a uniform background can be effectively restrained, and therefore the probability of missing detection and false detection is remarkably reduced.

The invention relates to the technical field of liquid crystal display, in particular to a high-contrast Mini-LED backlight module which comprises a Mini-LED lamp panel, a reflecting cover is arranged on the Mini-LED lamp panel, an injection molding diffusion plate is arranged right above the reflecting cover, and a liquid crystal layer is arranged on the injection molding diffusion plate. A first light condensation structure in the X direction and a second light condensation structure in the Y direction are arranged on the face, close to the reflection cover, of the injection molding diffusion plate, and a third light condensation structure is formed at the joint of the first light condensation structure and the second light condensation structure. According to the backlight module and the manufacturing method thereof, through the design of the special condensation structure at the position, corresponding to the ridge of the reflecting cover, on the injection-molded diffusion plate, light rays propagating into adjacent partitions at a large angle are blocked, the light rays are emitted above the ridge of the reflecting cover, display halo is optimized, and the backlight module with the ultrahigh contrast ratio is obtained. And meanwhile, latticed display light and dark stripes caused by the ridge structures are eliminated, and the reflecting cover structure is effectively shielded, so that the design requirements of the reflecting cover structure are reduced, the process is simplified, the cost is optimized, and the requirements of more products and users are met.

To provide an onium salt for use in a chemically amplified resist composition that exhibits high solvent solubility, high sensitivity, and high contrast in photolithography using high-energy radiation, while also offering superior lithography properties such as exposure latitude (EL) and line width roughness (LWR); a chemically amplified resist composition comprising the onium salt as a photoacid generator; and a pattern forming process using the chemically amplified resist composition.SOLUTION: The present invention provides an onium salt represented by formula (1).SELECTED DRAWING: None

The invention discloses a solution immersion type fingerprint detection method based on AIEgens, which comprises the step of carrying out immersion type fluorescent fingerprint detection based on the aggregation-induced emission effect of an organic fluorescent compound TPP-APBP-P. TPP is used as a luminous substrate, a long chain is connected to the luminous substrate to improve the lipophilicity of the luminous substrate, TPP-APBP-P is obtained, meanwhile, the PH of a solution is adjusted to improve the hydrophilicity of the luminous substrate, and finally the detection effect of the luminous substrate on potential fingerprints is improved; the fingerprint detector has very excellent detection effects on fingerprints in a high-temperature environment and aged fingerprints, and has high contrast, high sensitivity and high precision on fingerprint development.

The invention discloses a multifunctional display panel, a display device and a driving method.The multifunctional display panel comprises a dimming box, an electronic ink screen and a color display screen which are sequentially arranged in a stacked mode; the electronic ink screen comprises an opposed substrate, a first array substrate and an ink capsule, a first pixel electrode is arranged on the first array substrate, a first common electrode matched with the first pixel electrode is arranged on the opposed substrate, a first side electrode and a second side electrode which are parallel to each other are arranged between the opposed substrate and the first array substrate, and the ink capsule is arranged between the first side electrode and the second side electrode. The first side electrodes and the second side electrodes are alternately arranged, and the ink capsules are located between the adjacent first side electrodes and second side electrodes. The display panel not only can realize wide and narrow view angle switching, but also can realize switching between reflection display of a black-and-white picture and transmission display of a color picture, can also realize a high-contrast display mode, and is wide in function so as to be suitable for more use scenes.

This invention discloses a quantum entangled light spatial correlation imaging method based on iterative deconvolution, belonging to the field of quantum information. The method includes the following steps: illuminating the target sample with a position-momentum entangled light source, and acquiring multiple frames of entangled light carrying sample information using a single-photon camera; performing statistical operations on the acquired multi-frame images to remove irrelevant background noise and obtain a joint probability distribution image of the sample; extracting the correlation width using the spatial distribution image of the joint probability distribution through differential coordinate projection to construct the point spread function of the optical system; using the point spread function for forward convolution projection and backward error projection, updating the image estimate through iterative calculation until the convergence condition is met to obtain the target sample image. This invention utilizes a camera to image with a position-momentum entangled light source under low illumination conditions, which can obtain high-contrast target imaging and has potential advantages in imaging light-sensitive samples.

This invention relates to a polyamide composite material, its preparation method, and its applications. The polyamide composite material comprises the following components by weight: 55-75 parts polyamide resin, 15-35 parts glass fiber, 7-17 parts halogen-free flame retardant, 0.1-1 parts nucleating agent, 0.1-0.7 parts colorant, and 0.1-0.6 parts lubricant. The nucleating agent comprises a linear saturated sodium carboxylate with a carbon chain length of C28-C32. The polyamide composite material provided by this invention exhibits high blackness, enables high-contrast ultraviolet laser marking, and possesses excellent mechanical and flame-retardant properties, making it suitable for ultraviolet laser marking in the electronics and electrical appliance fields.

An uneven region is extracted with high precision from a captured image obtained by capturing an image of a dyed knitted fabric, and the dyeing quality of the knitted fabric is evaluated. An edge in a captured image of a captured knitted fabric is detected, a high-contrast region in which the gradient of the edge (11) is equal to or greater than a first predetermined value is extracted, and a non-uniform candidate region serving as a candidate for a non-uniform region is extracted from the high-contrast region (steps S105-S107). On the other hand, in the captured image, a plurality of highly similar regions having high similarities with the sample image of the trunk are extracted, information on the positions of representative points of the trunk corresponding to each of the highly similar regions is acquired, and information on the positions of the trunk is acquired on the basis of the information on the positions of the representative points (steps S108-S110). Afterwards, among the non-uniform candidate regions, regions that extend continuously in the course direction across a predetermined number or more of trunks are extracted as non-uniform regions (step S111), and the dyeing quality of the knitted fabric is evaluated on the basis of the extracted non-uniform regions (step S112).