Abstract: A pattern defect inspection method includes generating electron beam irradiation point track data on the basis of first data on an inspection target pattern, irradiating the electron beam to the inspection target pattern in accordance with the electron beam irradiation point track data, detecting secondary electrons generated from the inspection target pattern due to the irradiation of the electron beam, acquiring second data regarding a signal intensity of the secondary electrons from a signal of the detected secondary electrons, and detecting an abnormal point from the second data and outputting the abnormal point as a defect of the inspection target pattern. The electron beam irradiation point track data includes data on a track of irradiation points of an electron beam to the inspection target pattern and is intended to control over scanning with the electron beam, the electron beam irradiation point track data.

Abstract: In one embodiment, a pattern inspection method is disclosed. The method can include predicting an edge shape at a given future time with respect to the same inspection target pattern, setting a threshold corresponding to a required specification of the inspection target pattern, and predicting the time when the inspection target pattern fails to meet the required specification from the predicted edge shape and the threshold. The method can further include taking a plurality of images concerning the inspection target pattern at different times by use of an imaging apparatus, detecting edges of the obtained images, respectively, matching the detected edges of different imaging times, and obtaining a difference between corresponding edges to generate a difference vector after the matching. The edge shape of the future time can be predicted based on the generated difference vector and an interval between the imaging times.

Abstract: In accordance with an embodiment, a pattern evaluation system includes an image acquisition unit, a plurality of image processing units, and a control unit which controls the plurality of image processing units. The image acquisition unit loads a series of images of a pattern to be evaluated. The images are acquired at a first speed. The plurality of image processing units process the series of images at a second speed and then output a result of the evaluation of the pattern to be evaluated. The control unit acquires the first and second speeds, estimates the number of the image processing units which allow the time for acquiring the series of images to be substantially the same as the time for processing the series of images, and allocates the estimated image processing units to the processing of the series of images.

Abstract: A defect inspection method includes: acquiring an image of an inspection pattern obtained by an imaging device, detecting an edge of the inspection pattern in the image, dividing the image into an inspection region and a non-inspection region, using the detected edge as a boundary thereof, performing image processing only on the inspection region to determine the intensity value distribution in the image, and detecting a defect in the inspection pattern based on the obtained intensity value distribution.

Abstract: A pattern shape evaluation method comprising detecting an edge of an evaluation target pattern from an image of the evaluation target pattern to output the edge as a first edge, detecting an edge of a reference pattern from an image of the reference pattern to output the edge as a second edge, performing a relative scan of the first edge and the second edge to superpose the first edge onto the second edge, and outputting a resulting edge as a third edge, calculating a characteristic amount indicating characteristics of the third edge from the third edge, and deriving a characteristic amount function which provides the characteristic amount against relative coordinates in the relative scan and comparing the characteristic amount function with a preset value to judge whether or not the evaluation target pattern is good.

Abstract: An image processing apparatus which compresses an image, the apparatus includes: a storage unit which stores a code book, the code book being prepared by allocating identification codes to code blocks, the code blocks being formed by executing quantization processing regarding a plurality of first image blocks as multidimensional vectors, the plurality of first image blocks being generated by cutting, in preset sizes, first regions out of a code book preparation image containing a first edge, each of the first regions surrounding and including an edge point of the first edge, the first edge being detected from the code book preparation image; an edge detection unit which detects a second edge from a compression target image containing the second edge; an image block generation unit which cuts, in preset sizes, second regions out of the compression target image to generate a plurality of second image blocks, each of the second regions surrounding and including an edge point of the detected second edge; a searc

Abstract: A pattern evaluation method includes: acquiring data of a design pattern for an evaluation pattern to detect a first edge of the design pattern; acquiring an image of the evaluation pattern to detect a second edge of the evaluation pattern; dividing the first edge into first linear parts and first corner parts; performing matching of the first and second edges to obtain correspondence between the first and second edges; dividing the second edge into second linear parts and second corner parts based on the correspondence between the first and second edges; and evaluating the evaluation pattern based on at least one of the second linear parts and the second corner parts.

Abstract: A pattern measurement method includes: acquiring sectional shapes of a first pattern corresponding to process parameters, respectively; using the acquired sectional shapes to calculate predicted spectral waveforms which would be obtained when light is applied to the first pattern, and adding information on the corresponding process parameters to the calculated predicted spectral waveforms, respectively, to form a waveform library; setting a process parameter to obtain a desired shape, and acquiring an actual spectral waveform of a second pattern actually created from the first pattern using the set process parameter; performing waveform matching between the actual spectral waveform and the predicted spectral waveforms to acquire matching scores for respective waveform matching, and calculating an optimum process parameter providing the maximum matching score; generating an optimum pattern sectional shape corresponding to the optimum process parameter to measure the optimum pattern sectional shape.

Abstract: A pattern defect inspection method includes generating electron beam irradiation point track data on the basis of first data on an inspection target pattern, irradiating the electron beam to the inspection target pattern in accordance with the electron beam irradiation point track data, detecting secondary electrons generated from the inspection target pattern due to the irradiation of the electron beam, acquiring second data regarding a signal intensity of the secondary electrons from a signal of the detected secondary electrons, and detecting an abnormal point from the second data and outputting the abnormal point as a defect of the inspection target pattern. The electron beam irradiation point track data includes data on a track of irradiation points of an electron beam to the inspection target pattern and is intended to control over scanning with the electron beam, the electron beam irradiation point track data.

Abstract: A pattern shape evaluation method includes acquiring an image of an evaluation target pattern including a plurality of element patterns; detecting edge of the evaluation target pattern from the image; classifying the detected edge of the evaluation target pattern into a plurality of evaluation target pattern edge groups; acquiring edge of a reference pattern serving as an evaluation standard for the element patterns; classifying the edge of the reference pattern into a plurality of reference pattern edge groups; selecting a reference pattern edge group to be aligned with the edge of the evaluation target pattern from the classified reference pattern edge groups; aligning the edge of the selected reference pattern edge group with the edge of the evaluation target pattern; and evaluating the shape of the evaluation target pattern by use of the result of the alignment.

Abstract: A pattern misalignment measurement method includes acquiring an inspection image of a composite pattern formed by superposing a plurality of kinds of element patterns on each other, acquiring reference images of at least two kinds of element patterns from reference images which are images of reference patterns of the plurality of kinds of element patterns, performing first matching of each of the acquired reference images with the inspection image, and outputting misalignment between the element patterns in the composite pattern on the basis of the result of the first matching.

Abstract: A pattern evaluation method includes: generating first array data from edge data on a pattern to be evaluated, the edge data on the pattern to be evaluated being shape data including edge points of the pattern to be evaluated; generating second array data from edge data on a reference pattern, the edge data on the reference pattern including edge points of the reference pattern which serves as an inspection standard of the pattern to be evaluated; subjecting each component of the second array data to array conversion processing, the array conversion processing being designed to convert a value of the component of the second array data into a function value of a value of a distance from that component to the edge point closest thereto, thereby generating third array data; executing arithmetic processing between the first array data and the third array data to generate fourth array data; and using a component of the fourth array data to calculate a numerical value representative of an relation between the patte

Abstract: In one embodiment, a pattern inspection method is disclosed. The method can include predicting an edge shape at a given future time with respect to the same inspection target pattern, setting a threshold corresponding to a required specification of the inspection target pattern, and predicting the time when the inspection target pattern fails to meet the required specification from the predicted edge shape and the threshold. The method can further include taking a plurality of images concerning the inspection target pattern at different times by use of an imaging apparatus, detecting edges of the obtained images, respectively, matching the detected edges of different imaging times, and obtaining a difference between corresponding edges to generate a difference vector after the matching. The edge shape of the future time can be predicted based on the generated difference vector and an interval between the imaging times.

Abstract: An image processing apparatus which compresses an image, the apparatus includes: a storage unit which stores a code book, the code book being prepared by allocating identification codes to code blocks, the code blocks being formed by executing quantization processing regarding a plurality of first image blocks as multidimensional vectors, the plurality of first image blocks being generated by cutting, in preset sizes, first regions out of a code book preparation image containing a first edge, each of the first regions surrounding and including an edge point of the first edge, the first edge being detected from the code book preparation image; an edge detection unit which detects a second edge from a compression target image containing the second edge; an image block generation unit which cuts, in preset sizes, second regions out of the compression target image to generate a plurality of second image blocks, each of the second regions surrounding and including an edge point of the detected second edge; a searc

Abstract: A pattern edge detecting method includes: detecting edge points in an image of an inspection pattern acquired from an imaging device; generating a plurality of edge lines from the edge points using a grouping process; generating a plurality of edge line group pairs, each composed of a combination of first and second edge line groups to be a candidate of any of one and the other of an outside edge and an inside edge of the inspection pattern, the generated edge lines being divided into two parts in different manners; performing shape matching between the first and second edge line groups for each edge line group pair; and specifying, as an edge of the inspection pattern, one of the first and second edge line groups constituting the edge line group pair whose matching score is best of matching scores of the edge line group pairs obtained during the shape matching.

Abstract: A pattern evaluation method includes: acquiring a plurality of examination images obtained in regard to an evaluation target pattern, at least one of the plurality of examination images being different from the other examination images; detecting all edges of the evaluation target pattern in each of the examination images; executing alignment of the evaluation target pattern in the respective examination images with a sub-pixel accuracy based on the detected edges; superimposing the aligned pattern edges to generate a single combined edge; measuring the combined edge; and evaluating the evaluation target pattern based on a result of the measurement.

Abstract: A pattern matching method includes: detecting an edge of a pattern in a pattern image obtained by imaging the pattern; segmenting the detected pattern edge to generate a first segment set consisting of first segments; segmenting a pattern edge on reference data which serves as a reference for evaluating the pattern to generate a second segment set consisting of second segments; combining any of the segments in the first segment set with any of the segments in the second segment set to define a segment pair consisting of first and second segments; calculating the compatibility coefficient between every two segment pairs in the defined segment pairs; defining new segment pairs by narrowing down the defined segment pairs by calculating local consistencies of the defined segment pairs on the basis of the calculated compatibility coefficients and by excluding segment pairs having lower local consistencies; determining an optimum segment pair by repeating the calculating the compatibility coefficient and the defini

Abstract: An image processing apparatus which compresses an image, the apparatus includes: a storage unit which stores a code book, the code book being prepared by allocating identification codes to code blocks, the code blocks being formed by executing quantization processing regarding a plurality of first image blocks as multidimensional vectors, the plurality of first image blocks being generated by cutting, in preset sizes, first regions out of a code book preparation image containing a first edge, each of the first regions surrounding and including an edge point of the first edge, the first edge being detected from the code book preparation image; an edge detection unit which detects a second edge from a compression target image containing the second edge; an image block generation unit which cuts, in preset sizes, second regions out of the compression target image to generate a plurality of second image blocks, each of the second regions surrounding and including an edge point of the detected second edge; a searc

Abstract: A pattern shape evaluation method for deciding whether a pair of patterns are disconnected or connected. The method includes extracting a plurality of pattern contour points that make up a contour of a pattern in a measurement region, and creating two pattern contour point sequences based on the plurality of pattern contour points. Each of the two pattern contour point sequences includes a set of the pattern contour points. In the pattern contour point sequence, each of distances between neighboring pattern contour points is equal to or smaller than a predetermined value. The method includes calculating an angle between a line passing through two of the pattern contour points which provide a shortest distance between the two pattern contour point sequences and a reference line arbitrarily defined with respect to the measurement region. The method further includes deciding whether the patterns are disconnected or connected, based on the angle.

Abstract: In accordance with an embodiment, a pattern evaluation system includes an image acquisition unit, a plurality of image processing units, and a control unit which controls the plurality of image processing units. The image acquisition unit loads a series of images of a pattern to be evaluated. The images are acquired at a first speed. The plurality of image processing units process the series of images at a second speed and then output a result of the evaluation of the pattern to be evaluated. The control unit acquires the first and second speeds, estimates the number of the image processing units which allow the time for acquiring the series of images to be substantially the same as the time for processing the series of images, and allocates the estimated image processing units to the processing of the series of images.