742 results about "Defect region" patented technology

An automatic, red-eye detection and correction system for digital images capable of real-time processing of images, including a red-eye detector module that determines without user intervention if a red-eye defect exists. If a defect is located in an image the portion of the image surrounding the defect is passed to a correction module that de-saturates the red components of the defect while preserving the other color characteristics of the defect region. The invention is designed to minimize the computational resources required to detect and correct red-eye defects and thus is particularly suited to applications requiring real-time processing of large volumes of digital images prior to acquisition or printing. This system can operate on images stored on personal computers, commercial printers or inside digital cameras as part of the acquisition process, or prior to display on personal digital assistants, mobile phones and other digital imaging appliances.

A multi-layered information recording medium including a plurality of recording layers, the multi-layered information recording medium comprising: a user data area for recording user data; and a plurality of spare areas including at least one replacement region, wherein when the user data area includes at least one defect region, the at least one replacement region may be used in place of the at least one defect region, wherein a first spare area of the plurality of spare areas is positioned so as to be contiguous to a first user data area of a first recording layer, a second spare area of the plurality of spare areas is positioned so as to be contiguous to a second user data area of a second recording layer, and the first spare area and the second spare area are positioned approximately at the same radial position on the multi-layered information recording medium.

A method for digital image eye artifact detection and correction include identifying one or more candidate red-eye defect regions in an acquired image. For one or more candidate red-eye regions, a seed pixels and / or a region of pixels having a high intensity value in the vicinity of the candidate red-eye region is identified. The shape, roundness or other eye-related characteristic of a combined hybrid region including the candidate red-eye region and the region of high intensity pixels is analyzed. Based on the analysis of the eye-related characteristic of the combined hybrid region, it is determined whether to apply flash artifact correction, including red eye correction of the candidate red-eye region and / or correction of the region of high intensity pixels.

The present invention refers to a method for automatically correcting color defective areas in an image, which defective color areas were recorded with a color spectrum deviating from the actual color spectrum of said areas without color defects, wherein basic areas in the image are identified on the basis of features which are common for these recorded defective areas, said basic areas supporting an increased likelihood to include defective areas, and the processing is then reduced to the basic areas to identify borderlines and / or centres of the defective areas, and afterwards, it is identified whether the localized basic area or areas deemed to be defective are defective or not, and finally, if a localized basic area has been identified to be defective, a correction mask is created to correct the visual appearance of the defective area.

The present invention relates to a method of detecting a defect area without any mistake during data recording on a writable disk. This method detects a level of a servo error signal produced during a recording operation, checks whether the servo error signal is in an abnormal state based on the detected level, detects a periodic wobble signal or periodicity of the abnormal state occurrences of the servo error signal produced during the recording operation, and determines whether a recording area is in defect based on successful decoding of the detected periodic wobble signal or the periodicity of the abnormal state occurrences if the servo error signal is in an abnormal state. This method ensures exact detection of a defect area, whereby unnecessary speed reduction can be eliminated and successful data writing can be also guaranteed even in a defect area.

A rewritable optical medium and a method of managing its defect area is disclosed. The DMA condition or initially assignable spare area size in the present invention is determined based upon the interrelation between the spare area size and the DMA condition. Namely, the PDL entry condition among the DMA condition is determined to allow a minimum spare area for linear replacement in the initially assignable spare area after slipping replacement during formatting to facilitate management of the defect area of a rewritable optical medium. The present invention also discloses a method of controlling the recording / playback of optical media with the same format and different sizes, thereby improving the system performance.

A method for red-eye detection in an acquired digital image acquiring one or more preview or other reference images without a flash. Any red regions that exist within the one or more reference images are determined. A main image is acquired with a flash of approximately a same scene as the one or more reference images. The main image is analyzed to determine any candidate red eye defect regions that exist within the main image. Any red regions determined to exist within the one or more reference images are compared with any candidate red eye defect regions determined to exist within the main image. Any candidate red eye defect regions within the main image corresponding to red regions determined also to exist within the one or more reference images are removed as candidate red eye defect regions.

The present invention provides a semiconductor device capable of suppressing a body floating effect, and a manufacturing method thereof. A semiconductor device having an SOI structure includes a silicon substrate, a buried insulating layer formed on the silicon substrate, and a semiconductor layer formed on the buried insulating layer. The semiconductor layer has a body region of a first conduction type, a source region of a second conduction type and a drain region of the second conduction type, and a gate electrode is formed on the body region between the source region and the drain region via a gate oxide film. The source region includes an extension layer of the second conduction type, and a silicide layer which makes contact with the extension layer at its side face, and a crystal defect region is formed on a region of a depletion layer generated in a boundary portion between the silicide layer and the body region.

This method of removal of irregularities and highly defected regions of the surface of crystals and epitaxial layers of GaN and Ga1-x-yAlxInyN characterized by mechano-chemical polishing on the soft polishing pad under pressure in presence of chemical etching agent of water solution of bases of the total concentration above 0.01N in time longer than 10 seconds after which the agent is replaced by the pure water without interruption of the polishing and polishing by at least 1 minute aid subsequent diminution of the load and stopping of the machine and then the polished GaN crystal or GaAlInN epitaxial layer is removed of the polishing machine and dried in the stream of dry nitrogen.

The invention discloses a multi-vision defect detecting equipment and a multi-vision defect detecting method for a large-size LCD glass substrate in a production line. For the equipment, a linear scanning imaging detection system is adopted for acquiring the high-definition gray image of an LCD glass substrate to be detected, and the equipment is simple in structure and convenient to operate; according to the method disclosed by the invention, the acquired image is processed, a kmeans clustering method is adopted to carry out defect existence judgment on the processed image of the LCD glass substrate, and by making the defect regions, the defect category is judged by a classification method of a support vector machine (SVM), and the defect quantity is counted. Processed image and detection results are transmitted to an office in real time by a filed bus control system for operators on duty to check, and the field production parameters are transmitted, so that remote monitoring of the system is realized.

A defect detection apparatus (1) comprises an image pickup part (3) for picking up an image of a substrate (9) to acquire a grayscale target image, from which pixel values of the target image are sequentially outputted to a defect detector (43). The defect detector (43) compares the target image with a reference image to generate a defect region image representing regions of defects included in a plurality of predetermined inspection regions, to be stored in a defect region image memory (44). A computer (5) obtains an area and a barycentric position of each of the defects in the defect region image to specify an inspection region including the defect and performs limitation (i.e., selection) of defects on the basis of a defect detection condition set for each inspection region on the area of defect. It is possible to detect defects with high efficiency by using a defect detection condition on a different area of defect for each inspection region.

The invention discloses a fabric defect detection method based on a deep convolution neural network and visual saliency, which belongs to the technical field of image processing. A defect region positioning module and a defect semantic segmentation module are included. The defect region positioning module uses two deep learning models of a local convolution neural network and a global convolutionneural network for fusion, advanced features of a fabric defect are extracted automatically and act on a defect image, and precise positioning of the defect region is acquired. The defect semantic segmentation module uses the defect region positioning result, a super pixel image segmentation method based on visual saliency is combined, a defect prior foreground point is acquired, a defect target is precisely segmented, and defect detection is finally realized. The multi-deep learning-fused fabric defect positioning network and the improved fabric defect segmentation network based on the visualsaliency are used, the adaptability to the fabric image is good, the precision is high, and defects in the fabric image under a complex background and noise interference can be effectively detected.

An image is acquired including a red eye defect and non red eye defect regions having a red color. An initial segmentation of candidate redeye regions is performed. A location and orientation of one or more faces within the image are determined. The candidate redeye regions are analyzed based on the determined location and orientation of the one or more faces to determine a probability that each redeye region appears at a position of an eye. Any confirmed redeye regions having at least a certain threshold probability of being a false positive are removed as candidate redeye defect regions. The remaining redeye defect regions are corrected and a red eye corrected image is generated.

In a nitride semiconductor light-emitting device, and according to a method for fabricating it, a low-defect region having a defect density of 106 cm−2 or less and a carved region in the shape of a depressed portion are formed on the surface of a nitride semiconductor substrate, and the etching angle θ, which is the angle between the side surface portion of the depressed portion and an extension line of the bottom surface portion thereof as measured with the depressed portion seen in a sectional view, is in a range of 75°≦θ≦140°. This prevents the development of cracks, and reduces the creep-up growth from the bottom growth portion of the carved region, thereby reducing the film thickness of the side growth portion. This makes it possible to produce, with a high yield, a nitride semiconductor laser device having a nitride semiconductor growth layer with good surface flatness.

The invention relates to a method and device for rapidly detecting and classifying defects of a glass image, wherein the method comprises the steps of: 1, scanning windows of an input glass image, measuring according to the balance of gray level distribution in the windows to obtain candidate defect windows; 2, merging the adjacent candidate defect windows according to the position relationship of the candidate defect windows to obtain a candidate defect region; 3, obtaining background information of the candidate defect region, and extracting a defect domain according to the gray level distribution mode of the candidate defect region; and 4, normalizing the defect domain according to the scale, extracting characteristic vectors, and classifying the defects according to the characteristic vectors to obtain a defect classifying result. By adopting the method, the defects in a glass image frame containing the noise can be accurately detected, the class of the defects can be effectively distinguished and the undefined defects can be judged.

An optical disc of write once type, a method and an apparatus of managing defect information on the optical disc of write once type, e.g., a BD-WO, are provided with a temporary defect management area (TDMA). The method includes preparing the temporary defect management area (TDMA) in which a temporary defect list (TDFL) is recorded as defect management information for managing a defective area on the optical disc, recording the most recent temporary defect list cumulatively with the previous temporary defect list in the temporary defect management area, and recording position information for indicating a position of the most recent temporary defect list in the temporary defect management area along with the temporary defect list to more effectively manage the temporary defect list.

A non-volatile semiconductor memory device includes: a memory chip configured to be electrically rewritable and store such multi-level data as being defined by n-bits / cell (where n≧2); and a memory controller configured to control read and write of the memory chip, wherein the operation mode of the memory chip is changed from n-bits / cell to m-bits / cell (where m<n) when the number of late-generated defective areas is over a certain threshold value.

A semiconductor device has a two-dimensional slab photonic crystal structure in which a substrate supports a sheet-like slab layer including, sequentially stacked, a lower cladding layer, an active layer, and an upper cladding layer. A periodic refractive index profile structure, in surfaces of the stacked layers, introduces a linear defect region that serves as a waveguide. A p-type region and an n-type region in the slab layer define a pn junction surface at a predetermined angle with respect to the surfaces of the stacked layers in the slab layer.

A recording medium of writable once type, and a method and apparatus for managing a defective area on the recording medium are provided. The method includes detecting an existence of a defective area within a data area of the recording medium once data are written onto the data area in a data writing operation; writing data written in the defective area onto a spare area of the data area if the defective area is detected; writing temporary management information pertaining to the defective area, onto a temporary management area on the recording medium; and writing access information for accessing the temporary management information, onto a reserved area on the recording medium.

A process for bonding oxide-free silicon substrate pairs and other substrates at low temperature. This process involves modifying the surface of the silicon wafers to create defect regions, for example by plasma-treating the surface to be bonded with a or boron-containing plasmas such as a B2H6 plasma. The surface defect regions may also be created by ion implantation, preferably using boron. The surfaces may also be amorphized. The treated surfaces are placed together, thus forming an attached pair at room temperature in ambient air. The bonding energy reaches approximately 400 mJ / m2 at room temperature, 900 mJ / m2 at 150° C., and 1800 mJ / m2 at 250° C. The bulk silicon fracture energy of 2500 mJ / m2 was achieved after annealing at 350-400° C. The release of hydrogen from B-H complexes and the subsequent absorption of the hydrogen by the plasma induced modified layers on the bonding surfaces at low temperature is most likely responsible for the enhanced bonding energy.

A method for identifying defective data sectors in a disk drive comprising generating a test pattern on a portion of a disk surface; reading the test pattern on the portion to detect an error and if an error is detected: associating the error with a physical location on the portion to identify a defective area unsuitable for user data; and assigning a severity category to the defective area. The method further comprises providing a physical defect list (P-list) for listing each defective area, the P-list having a predetermined limit to restrict a number of P-list entries; and posting the defective areas having a first severity category to the P-list and if the P-list limit is not exceeded by the first severity category entries: posting defective areas having a second severity category to the P-list.

A digital image acquisition and processing system that automatically corrects dust artifact regions within acquired images by compiling a statistical dust map from multiple images acquired under different image acquisition conditions is provided. The system includes a digital camera and an external processing device. The camera includes an optical system for acquiring an image including a lens assembly and an aperture stop, and an electronic sensor array disposed approximately at an image focal plane of the optical system for collecting image data according to spectral information associated with multiple pixels that collectively correspond to the image. The external processing device couples with the digital camera to receive the image data or converted image data internally processed within the digital camera. The external device includes digital processing electronics including a processor for processing the image data according to programming instructions. The system includes one or more memories having programming instructions stored therein for performing a method of automatic image correction of dust defect regions.

The invention relates to a rapid imaging detection method for gear appearance defects. The rapid imaging detection method comprises two stages including a pre-processing stage and an online detection stage. The pre-processing stage comprises three procedures including automatically setting a target region, generating a coarse detection template and generating a fine detection template. The online detection stage comprises the steps of: J1) acquiring an image; J2) preprocessing and extracting features; J3) carrying out area difference value calculation on the image to be detected and an image of the coarse detection template for coarse detection judgment; J4) registering the image to be detected and an image of the fine detection template so that gear tooth directions of the two images are coincided; J5) and carrying out exclusive-or operation on the image to be detected and the image of the fine detection template to obtain a differential image, and acquiring defect region area in the differential image for fine detection judgment. The rapid imaging detection method for gear appearance defects acquires images by utilizing machine vision, performs coarse and fine judgment by utilizing template matching and image exclusive-or operation, and is high in detection precision and fast in speed.