7 results about "Multi focus" patented technology

A multi-focal ophthalmic lens using suppressed diffraction orders. A multi-focal ophthalmic lens includes an ophthalmic lens and a diffractive element. The ophthalmic lens has a base curvature corresponding to a base power. The diffractive element produces constructive interference in at least four consecutive diffraction orders corresponding to a range of vision between near vision and distance vision. The constructive interference produces a near focus point, a distance focus point, and an intermediate focus point between the near focus point and the distance focus point corresponding to the base power of the ophthalmic lens. The diffraction efficiency of at least one of the diffraction orders is suppressed to less than 10%.

The application relates to the technical field of precision part detection, and discloses a precision part defect intelligent detection method based on deep learning. A multi-focus image sequence of a part surface is acquired, a multi-scale feature map set is generated through pyramid multi-scale decomposition, defect edge and texture information is extracted, a defect candidate region is determined, the feature map set is fused in combination with an attention mechanism, enhanced defect feature representation is generated, defect projection coordinates are extracted and depth values are calculated, a three-dimensional space position of the defect is acquired, a part surface geometric model is reconstructed, and a defect boundary curve is extracted, the defect width is calculated based on the boundary curve, an abnormal width section is identified and the defect change is tracked, the defect stability is judged, the image acquisition parameters are adjusted according to the defect stability, and optimized multi-focus image sequence acquisition is realized. The application realizes full-process intelligent detection of surface cracks from feature extraction, three-dimensional positioning to dynamic tracking, and significantly improves the detection precision and reliability.

This invention relates to the field of microscopic optical imaging technology, specifically to a multi-dimensional encoded long focal depth optical field two-photon microscopic imaging method and system. The method and system include: designing a multi-dimensional encoded optical field, configured to flexibly adjust the intensity and position distribution of the optical field based on multifocal spatial multiplexing; inserting an optical field distribution shaping module into a traditional two-photon imaging system to change the phase position relative to the objective lens's back aperture; performing two two-dimensional scans of the sample based on the multi-dimensional encoded optical field scanning imaging to obtain two two-dimensional projection images, which are then determined by combining the lateral spacing distribution of the projection points and the fluorescence intensity ratio. This invention can simultaneously encode the sample distribution into the multi-dimensional information of intensity and position distribution in the projection images during the scanning imaging process, achieving efficient and rapid three-dimensional imaging by analyzing and locating the sample's three-dimensional distribution, improving the accuracy of sample depth analysis, and accelerating the three-dimensional imaging of the sample.

This invention provides a multi-focus head-up display system and method for solving the visual fatigue problem that occurs with automotive head-up displays and for realizing augmented reality functionality. [Solution] A multi-focus augmented reality head-up display system including: an image projector that generates and emits multiple beams; an optical device that guides the multiple beams emitted from the image projector to their respective paths; a polarization adjustment device that adjusts the polarization state of the multiple beams incident from the optical device; and multiple HOEs (Holographic Optical Elements) that each receive the multiple beams emitted from the polarization adjustment device and project virtual image planes at different focal lengths.

The application relates to the technical field of deep learning, and discloses a precision manufacturing surface defect detection method based on deep learning. The method comprises the following steps: acquiring a multi-focus image sequence of a manufacturing component, extracting macroscopic contour features and generating a preliminary depth map, fusing the preliminary depth map with multi-source sensing data, and constructing a comprehensive three-dimensional model of the manufacturing component; performing pixel-level semantic segmentation on the comprehensive three-dimensional model, generating an enhanced texture map, extracting stereo parameters, and calculating a quantitative value of a surface quality index of the manufacturing component by using a nonlinear regression model; judging whether the quantitative value exceeds a preset tolerance range, and if the quantitative value exceeds the preset tolerance range, adjusting parameters of a three-dimensional reconstruction process until an optimized three-dimensional reconstruction result with a qualified quantitative value is obtained; based on the qualified three-dimensional reconstruction result, fusing macroscopic and microscopic features to generate a defect distribution mapping diagram, identifying a surface defect type, and obtaining a surface quality evaluation report, and the application improves the detection accuracy of surface defects of the manufacturing component.

This invention relates to the fields of digital image processing and semiconductor automated inspection technology, specifically disclosing a multi-focus image fusion method and system for semiconductor packaging bonding processes. This invention utilizes a GPU to run a semantic segmentation model to generate a mask, driving non-uniform layered sampling with key area encryption and background area sparseness along the Z-axis. It uses an FPGA to adjust the light source in real time based on the reflection ratio, constructing an active light source adaptive closed loop, and intelligently scheduling FPGA hardware interpolation or GPU deep learning generation branches for reflection repair. Finally, it combines edge, semantic, and attention metrics to construct a triple weight map, using a multi-scale pyramid strategy to achieve high- and low-frequency separation and fusion, realizing high-quality panoramic depth image generation suitable for Wirebond process AOI. This invention solves the problem of missed detection of micro-defects in semiconductor gold wire bonding inspection caused by strong reflection interference, low sampling efficiency, timing mismatch, and fusion distortion.

A color separation element and an image sensor including the same are disclosed. The color separation element includes a spacer layer, and a color separation lens array including at least one nano-post provided in the spacer layer to control a phase distribution of incident light so that light having the same wavelength of the incident light is multi-focused on a plurality of target regions; and periodic regions in which the phase distribution control layer is repeatedly arranged.