A multimodal inspection system (MIS) is disclosed herein. The MIS may use one or more modalities to inspect a sample. Some of the modalities include, but are not limited to, Raman, visible (VIS), terahertz (THz) spectroscopy, longwave infrared (LWIR), shortwave infrared (SWIR), laser profilometry (LP), electromagnetic interference (EMI) near field probing, and/or, Millimeter Wave (MMW) radar.

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.

In order to prevent an erroneous determination of an on-film defect, the sensitivity of the post-inspection is reduced so that a film swelling due to a minute defect would not be detected. Classification is performed to determine whether a defect is at least one of an on-film defect and a film swelling, by performing a coordinate correction on the result of a post-inspection by an actual-defect fine alignment using the result of a pre-inspection performed with two-stage thresholds, and by checking defects against each other. In addition, classification is performed to determine whether a defect is at least one of an on-film defect and a film swelling by, during the post-inspection, preparing instruction data from information of the refractive index and thickness of a film formed on a wafer and comparing the instruction data with a signal intensity ratio of a detection system.

A method for automatic defect classification, the method may include acquiring, by a first camera, at least one first image of at least one area of an object; processing the at least one first image to detect a group of suspected defects within the at least one area; performing a first classification process for initially classifying the group of suspected defects; determining whether a completion of a classification of the first subgroup of the suspected defects requires additional information from a second camera; when determining that the first subgroup of the suspected defects requires additional information from the second camera then: acquiring second images, by the second camera while applying image acquisition parameters of the second camera, to provide the additional information; and performing the second classification process for classifying the first subgroup of suspected defects.

A method for automatic defect classification, the method may include (i) acquiring, by a first camera, at least one first image of at least one area of an object; (ii) processing the at least one first image to detect a group of suspected defects within the at least one area; (iii) performing a first classification process for initially classifying the group of suspected defects; (iii) determining whether a first subgroup of the suspected defects requires additional information from a second camera for a completion of a classification; (iv) when determining that the first subgroup of the suspected defects requires additional information from the second camera then: (a) acquiring second images, by the second camera, of the first subgroup of the suspected defects; and (b) performing a second classification process for classifying the first subgroup of suspected defects.

There is provided a technique that includes: a camera configured to capture images of the target object; a memory configured to store the images of the target object and feature data including one or more predetermined exterior features of the target object; and a processor configured to: determine a first process configuration for an operation including a plurality of image processes; perform the operation under the first process configuration; generate inspection data from the sets of images that have been processed; generate an inspection score by comparing the inspection data with the feature data; compare the inspection score with a predetermined threshold score; set the first process configuration as an optimal configuration if the inspection score satisfies the predetermined threshold score.

According to one embodiment of the present invention, A sample inspection device may provided, a total inspection module scanning a first area comprising a plurality of samples; a precision inspection module performing inspection on a sample determined as a suspected defective sample by the total inspection module in the first area; and a controller processing each data obtained from the total inspection module and the precision inspection module, and detecting a defective sample in the first area, wherein the precision inspection module may include an emitter emitting terahertz wave to the first area, a guide wire guiding an irradiation direction of the terahertz wave, and a vibration unit vibrating the guide wire.

An image inspecting apparatus includes at least one image capturing part, a lighting part, a control part including a moving part, a searching part analyzing an image captured by the image capturing part under a first image capturing condition and searching for a defect candidate from an object under inspection, and a determining part. When the searching part finds the defect candidate from the object under inspection, the control part controls an image capturing condition such that a part where the defect candidate is found by the searching part is photographed under a second image capturing condition that is clearer than the first image capturing condition. The determining part analyzes an image captured by the image capturing part under the second image capturing condition and determines whether the defect of the object under inspection is present or absent.

Method and machine utilizes the real-time recipe to perform weak point inspection on a series of wafers during the fabrication of integrated circuits. Each real-time recipe essentially corresponds to a practical fabrication history of a wafer to be examined and/or the examination results of at least one examined wafer of same “lot”. Therefore, different wafers can be examined by using different recipes where each recipe corresponds to a specific condition of a wafer to be examined, even these wafers are received by a machine for examining at the same time.

Systems and methods for detecting defect candidates on a specimen are provided. One method includes, after scanning of at least a majority of a specimen is completed, applying one or more segmentation methods to at least a substantial portion of output generated during the scanning thereby generating two or more segments of the output. The method also includes separately detecting outliers in the two or more segments of the output. In addition, the method includes detecting defect candidates on the specimen by applying one or more predetermined criteria to results of the separately detecting to thereby designate a portion of the detected outliers as the defect candidates.