Abstract: A method and associated apparatus for relating a test image with a reference image in an automated image processing system is disclosed. The test and reference images are aligned. A two-dimensional scatter plot is then created by plotting the gray level of a test image pixel against the gray level of a corresponding reference image pixel for each aligned pixel location.

Abstract: A two-dimensional scatter plot is created by plotting the gray levels of pixels from a test image against the gray levels of corresponding pixels from a reference image. A noise reduction filter is applied on the scatter plot to define a mask shape which can be extracted and filled-in to generate a mask. Defect pixels on the test image are identified by comparing corresponding pixel gray values against the mask. A typical application is detecting defects in a semiconductor wafer during device fabrication.

Abstract: Disclosed is a fast and high resolution technique for estimating the skew angle in text document images. Detection of the skew angle is an important step in text processing tasks such as optical character reading (OCR) and computerized filing. The proposed method is based on the application of a recently developed algorithm for estimation of angle of straight lines in a scanned image. The Subspace-Based Line Detection (SLIDE) algorithm formulates the multi-line fitting problem in a special parameter estimation framework such that a signal structure similar to the one in the field of high-resolution sensor array processing is obtained. Then the well-studied techniques in that formalism (e.g., the ESPRIT algorithm) are exploited to produce closed-form and high resolution estimates for line parameters.

Abstract: Disclosed is a new self-reference signal processing technique for detecting the location of any nonregularities and defects in a periodic two-dimensional signal or image. Using high-resolution spectral estimation algorithms, the proposed technique first extracts the period and structure of repeated patterns from the image to sub-pixel resolution in both directions, and then produces a defect-free reference image for making comparison with the actual image. Since the technique acquires all its needed information from a single image, on the contrary to the existing methods, there is no need for a database image, a scaling procedure, or any apriori knowledge about the repetition period of the patterns.

Abstract: A new signal processing method solves the problem of fitting multiple lines in a two-dimensional image. The Subspace-Based Line Detection (SLIDE) algorithm formulates the multi-line fitting problem in a special parameter estimation framework such that a signal structure similar to the sensor array processing signal representation is obtained. Any spectral estimation method can then be exploited to obtain estimates of the line parameters. In particular, subspace-based algorithms of sensor array processing (e.g., the ESPRIT technique) can be used to produce closed-form and high resolution estimates for line parameters. The signal representation employed in this formulation can be generalized to handle both problems of line fitting (in which a set of binary-valued discrete pixels is given) and of straight edge detection (in which one starts with a grey-scale image).

Abstract: An image processor employing a camera, frame grabber and a new algorithm for detecting straight edges in optical images is disclosed. The algorithm is based on using a self-organizing unsupervised neural network learning to classify pixels on a digitized image and then extract the corresponding line parameters. The image processor is demonstrated on the specific application of edge detection for linewidth measurement in semiconductor lithography. The results are compared to results obtained by a standard straight edge detector based on the Radon transform; good consistency is observed; however, superior speed is achieved for the proposed image processor. The results obtained by the proposed approach are also shown to be in agreement with Scanning Electron Microscope (SEM) measurements, which is known to have excellent accuracy but is an invasive measurement instrument. The method can thus be used for on-line measurement and control of microlithography processes and for alignment tasks as well.