A light 2 for reflected light that emits visible light for reflected light onto a front side of a veneer 6, a light 32 for invisible light that emits near-infrared light for transmitted light onto a back side of the veneer 6, and an image processing device 1 that detects defects of the veneer 6 by analyzing a captured image generated by a line sensor camera 4 are provided. Defects of the veneer 6 are discriminated on the basis of a set of shading and shapes in an infrared-transmitted-light image based on the transmitted light, and colors in a visible-light image based on the reflected light. Consequently, even if a defect has a small color difference from a normal part in the visible-light image, difference of shading between the defective part and the normal part appears in the infrared-transmitted-light image, and a defect that is difficult to detect by seeing only a color difference in a visible-light image can be relatively easily detected.

An automatic determination process device 1 comprises image acquisition units 14, 147, 247, an automatic determination unit 15, and determination result output units 14, 148, 248. An error detection verification device 2 displays a defect candidate image on a display device. The error detection verification device 2 acquires, via an input device, secondary inspection determination result information about the defect candidate image. The image acquisition units 14, 147, 247 read the defect candidate image displayed by the error detection verification device 2 from a medium for displaying the same on the display device. The automatic determination unit 15 executes a determination process on the basis of the content of the defect candidate image read by the image acquisition units 14, 147, 247 and outputs a determination result. The determination result output units 14, 148, 248 generate a signal in accordance with the determination result. Said signal is equivalent to pressing, via the input device connected to the error detection verification device 2, either a “defect” button or a “good” button included on a screen displayed by the error detection verification device 2.

A measurement apparatus and a measurement method capable of speedily and accurately measuring an edge shape are provided. A measurement apparatus according to an aspect of the present disclosure includes an objective lens positioned so that its focal plane cuts across an edge part of a substrate, a detector including a plurality of pixels and configured to detect a reflected light from the edge part of the substrate through a confocal optical system, an optical head in which the objective lens and the detector are disposed, a moving mechanism configured to change a relative position of the optical head with respect to the substrate so that an inclination of the focal plane with respect to the substrate is changed, and a processing unit configured to measure a shape of the edge part.

This disclosure relates generally to a system and method for monitoring performance of low-cost sensors plied in a field for soil moisture measurement. The low-cost sensors are calibrated to give useful derived parameters to support farming such as volumetric water content (VWC) of the soil. Further, the steps are being incorporated to de-noise their response to derive stable measurements similar to expensive rugged sensors. The calibration of the low-cost sensor and normalization of incoming values from the low-cost sensor are based on values determined through rugged sensors for soil moisture measurement. The normalization involves finding a minimum value and maximum value of soil moisture. Performance of the low-cost sensors are analyzed based on a range of values of the soil moisture. Finally, the performance analysis provides degradation stages and based on the degradation stages evaluated recommendations to modify the sensor are shared with the user.

An apparatus for inspecting containers includes a rotation device which is adapted to rotate the container about the axis of symmetry; a camera sensitive to said predetermined electromagnetic radiation and with the container located in the field of view thereof; a processing unit to control the rotation device to move the container at a first angular speed constant for a first time period; acquiring at least a first and a second series of images of a portion of the container in a rotation thereof through 360′; to identify defective areas having at least one characteristic different from the characteristics of adjacent areas, generating first and second maps of the defective areas; to compare the position of the defective areas of the maps; to establish that first impurities are present in the container or in the liquid contained in the container.

A processing method includes obtaining a processing image of a apparatus and performing a second processing on the processing image to generate a target image to analyze the target image according to a target defect detection method to realize defect detection of the apparatus. The processing image is obtained by performing a first processing on an initial image of the apparatus. The first processing includes performing scale processing on the initial image according to defect parameters corresponding to the initial image.

A surface inspection apparatus includes an imaging device that images a surface of an object to be inspected, and a processor configured to: calculate an evaluation value of a texture of the object through processing of an image imaged by the imaging device; and detect reflection of a cause of erroneous calculation of the image within a specific range based on at least brightness information of the image.

A portable visual inspection apparatus comprises a box including a lower box portion and an upper box portion. The upper box portion defines a first accommodation space and is connected to the lower box portion such that is capable of being opened and closed. A visual inspection device is installed in the first accommodation space and is adapted to be switched between an expanded configuration in which the visual inspection device is at least partially expanded for photographing an image of an article, and a folded configuration in which the visual inspection device is at least partially folded for storage in the first accommodation space. A support platform is arranged in the lower box portion and defines an inspection area below the visual inspection device in the expanded configuration. The portable visual inspection apparatus is switchable between a use configuration and a transportation configuration.

An artificial neural network-based method for detecting a surface type of an object includes: receiving a plurality of object images, wherein a plurality of spectra of the plurality of object images are different from one another and each of the object images has one of the spectra; transforming each object image into a matrix, wherein the matrix has a channel value that represents the spectrum of the corresponding object image; and executing a deep learning program by using the matrices to build a predictive model for identifying a target surface type of the object. Accordingly, the speed of identifying the target surface type of the object is increased, further improving the product yield of the object.

A projection is determined in a semiconductor image, which can be an X projection and/or a Y projection. At least one threshold is applied to the projection thereby forming at least one segment within the region. A fine segment can be determined in the region using a distance value from the projection. Defect detection can be performed in one of the fine segments.