8 results about "Spin image" patented technology

The invention relates to the technical field of microlens detection, in particular to an automatic microlens detection method and system, and the method comprises the steps: obtaining a stripe image of a microlens under the illumination of a stripe structure; preprocessing the stripe image to obtain a preprocessed image with a block area as a foreground; determining a rotation angle according to the boundary of the reference block region, and rotating the corrected stripe image to align the stripe with the row direction; segmenting the rotating image, identifying a connected block, solving an external frame to generate a block mask and a complementary set interval mask thereof, and obtaining a block image and an interval image; performing segmentation on the block image, taking a median value according to rows to replace and generate a block reference image, performing differential binarization to obtain a block defect candidate, and performing independent binarization and merging on an abnormal region; overlapping the interval image and the block mask, performing closed operation to suppress line noise, and then performing binarization inversion to obtain an interval defect candidate; and superposing the two candidate output defect mark images. According to the invention, the defect can be automatically identified and marked and output by the microlens under the stripe background.

The application discloses a kind of based on motion compensation time domain filtering method for image, comprising: using autoregressive moving average model to the obtained gyroscope error is modeled, the change rule of data is used to estimate model parameter, and gyroscope error model is established;Using the gyroscope data of removing error obtained by gyroscope error model, the rotation matrix of camera is calculated, and the rotation image is compensated in reverse using rotation matrix, and the de-rotation image is obtained.Through kalman filtering to image motion vector sequence, image random jitter is obtained, and the de-rotation image is compensated according to random jitter, and the stable image and the subjective motion vector of image are obtained;Using the motion target detection algorithm in difference map based on large map coordinate system to detect target in stable image.The application has high detection sensitivity, and can detect target and its trajectory quickly through a small amount of frame track correlation.

The invention relates to a sea surface anti-flare method based on rotation polarization of an unmanned aerial vehicle, and the method comprises the steps: arranging a rotatable polarizing film in front of a lens of an image collection device, driving the polarizing film to rotate through a stepping motor, and enabling the image collection device to collect an image at a fixed frequency along with the rotation of the polarizing film; all the images collected by the polaroid in one rotation period are evaluated, the saturated pixel proportion, the contrast ratio and the information entropy of each image are calculated, a comprehensive evaluation function is established, the comprehensive evaluation functions of all the images in the period are compared, and the image with the optimal comprehensive evaluation function is screened out to serve as the optimal anti-blazing image. According to the method, the motor drives the polaroid to continuously rotate back and forth at a high speed, it is ensured that the polarization angle range of the polaroid is traversed in an extremely short time, image frames with the vibration transmission direction of the polaroid perpendicular to the main polarization direction of flare light can be captured inevitably, artifacts or information loss occurring in a traditional digital image processing method is avoided, and the image quality is improved. And efficient and reliable flare suppression capability is realized.

An image processing apparatus generates a corrected image to correct distortion in a captured image shot by an image capturing apparatus and obtains an internal parameter of the capturing apparatus based on a straight line edge in the corrected image. For parameter candidates serving as correct candidates for the internal parameter, a corrected image is generated by performing a perspective projection conversion on the captured image using the parameter candidate. One of the plurality of parameter candidates is obtained as the internal parameter of the capturing apparatus based on a straight line edge in each corrected image. For each of a plurality of rotated images obtained by rotating the corrected image by different rotation angles, obtained are a length of a vertical straight line edge in the rotated image, an evaluation value becoming higher as a total of the lengths obtained increases, and a parameter candidate providing a highest evaluation.

This application discloses an image correction model training method, image correction method, device, and storage medium. The model training method includes: acquiring feature information of an original image and acquiring a reference image corresponding to the original image; rotating the original image to obtain multiple rotated images, acquiring the inversion information of the rotated images, and constructing training samples from the multiple rotated images and their inversion information, along with the corresponding reference image; training a first preset neural network for predicting the inversion recognition information of the rotated images using the training samples; after training, inputting the rotated images into a second preset neural network to obtain a first corrected image; inputting the rotated images into the converged first preset neural network to obtain the inversion recognition information of the rotated images; obtaining a second corrected image based on the inversion recognition information and the first corrected image; completing the training of the second preset neural network to obtain an image correction model. Therefore, the complexity of the image correction model is reduced by recognizing the inversion information.

The invention discloses a nuclear industry CT image fine-grained defect identification method based on feature domain rotation consistency and dynamic constraint, and belongs to the technical field of computer vision and image processing. The method comprises the following steps: firstly, carrying out feature extraction on an original image and a rotating image thereof by utilizing a Vision Transform network to obtain corresponding Patch-level feature representation; and then restoring the Patch feature sequence into a two-dimensional feature map, and executing a rotation alignment operation in a feature space. Then, channel compression is carried out on the two-dimensional feature map after rotation alignment, local Patch features with overlapped areas are extracted in a sliding window mode, and Patch feature pairs corresponding to the spatial positions one by one are constructed; further, a dynamic threshold prediction mechanism is introduced, consistency constraint strength is adaptively set for different local areas, and only penalty is applied to feature differences exceeding a threshold, so that a rotation consistency loss function based on the dynamic threshold is constructed.

The embodiment of the invention provides a drug use detection processing method and device.The drug use detection processing method comprises the steps that in the drug use detection process, after a drug image obtained by conducting image collection on a drug before drug use is obtained, drug use detection is conducted in combination with the drug image and at least one pre-configured drug use task, after medicine use detection is passed, medicine use state information, recognized based on the rotation image sequence of the medicine after medicine use, of the user for the medicine is obtained, medicine use feedback processing is conducted on the associated user in combination with the medicine use state information and the corresponding medicine use feedback level, and therefore medicine use state recognition is achieved through the rotation image sequence of the medicine after medicine use; therefore, medicine use feedback is carried out to the associated user through the medicine use state information obtained through identification.

The invention relates to the technical field of image processing, discloses a medical instrument image processing method, and particularly relates to an endoscope rotation image processing method and an endoscope. According to the invention, the spatial position of the real-time image is updated to obtain the rotation image, the problem of image rotation caused by rotation of the endoscope is solved, and stable display of the image is realized. The parameters of the feature extraction module are dynamically adjusted by determining the rotation angle distribution result, so that the feature extraction process can adapt to the rotation change degree of the endoscope, and the accuracy and comprehensiveness of feature expression are improved. Moreover, image estimation is iteratively updated based on a regularization item of a convolution attention mechanism, spatial frequency information is captured in a convolution mode, a key area is focused in combination with the space and channel attention mechanism, image blurring is effectively removed, and the image restoration quality is improved. In addition, a pure rotation angle is accurately separated from the compound motion by an attitude calculation method based on quaternion and a spiral displacement method, so that the precision of rotation correction is ensured.