Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: There is provided a method, system and computer program product to delayer a layer of a sample, the layer comprising one or more materials, in an ion beam mill by adjusting one or more operating parameters of the ion beam mill and selectively removing each of the one or more materials at their respective predetermined rates. There is also provided a method and system for obtaining rate of removal of a material from a sample in an ion beam mill.

Abstract: A method and apparatus to reduce occurrences of electrically non-functional elements, known as dummy features, from a source data structure is described. The source data structure may be image data, a vector based data structure or some other data format. Dummy features in the source data structure are detected and then deleted. Dummy features may be detected by selecting a representative dummy feature, using it as a reference pattern or polygon and comparing it to features in the source data structure. The step of comparing the selected reference to the comprises selecting a cut-off correlation threshold value, and computing the correlation coefficients between the reference and the feature. Features are selectively removed based on a comparison between their correlation coefficients and the selected cut-off correlation threshold value. This threshold value may require updating to remove all dummy features in the source data structure.

Abstract: A method and apparatus to reduce occurrences of electrically non-functional elements, known as dummy features, from a source data structure is described. The source data structure may be image data, a vector based data structure or some other data format. Dummy features in the source data structure are detected and then deleted. Dummy features may be detected by selecting a representative dummy feature, using it as a reference pattern or polygon and comparing it to features in the source data structure. The step of comparing the selected reference to the comprises selecting a cut-off correlation threshold value, and computing the correlation coefficients between the reference and the feature. Features are selectively removed based on a comparison between their correlation coefficients and the selected cut-off correlation threshold value. This threshold value may require updating to remove all dummy features in the source data structure.

Abstract: The present invention involves a computationally efficient method of determining the locations of standard cells in an image of an IC layout. The initial step extracts and characterizes points of interest of the image. A coarse localization of possible standard cell locations is performed and is based on a comparison of the points of interest of an instance of an extracted standard cell and the remaining points of interest in the image. A more rigid comparison is made on the list of possible locations comprising a coarse match and a fine match. The coarse match results in a shortlist of possible locations. The fine match performs comparisons between the template and the shortlist. Further filtering is done to remove the effects of noise and texture variations and statistics on the results are generated to achieve the locations of the standard cells on the IC layout.

Abstract: A method and apparatus to reduce occurrences of electrically non-functional elements, known as dummy features, from a source data structure is described. The source data structure may be image data, a vector based data structure or some other data format. Dummy features in the source data structure are detected and then deleted. Dummy features may be detected by selecting a representative dummy feature, using it as a reference pattern or polygon and comparing it to features in the source data structure. The step of comparing the selected reference to the comprises selecting a cut-off correlation threshold value, and computing the correlation coefficients between the reference and the feature. Features are selectively removed based on a comparison between their correlation coefficients and the selected cut-off correlation threshold value. This threshold value may require updating to remove all dummy features in the source data structure.

Abstract: A method and apparatus to reduce occurrences of electrically non-functional elements, known as dummy features, from a source data structure is described. The source data structure may be image data, a vector based data structure or some other data format. Dummy features in the source data structure are detected and then deleted. Dummy features may be detected by selecting a representative dummy feature, using it as a reference pattern or polygon and comparing it to features in the source data structure. The step of comparing the selected reference to the comprises selecting a cut-off correlation threshold value, and computing the correlation coefficients between the reference and the feature. Features are selectively removed based on a comparison between their correlation coefficients and the selected cut-off correlation threshold value. This threshold value may require updating to remove all dummy features in the source data structure.

Abstract: The present invention provides a method and apparatus for reducing uneven brightness in an image from a particle based image system. This uneven brightness is most often seen as regions of shadow, but may also be seen as regions of over brightness. In cases where the uneven brightness is in the form of shadowing, the method corrects for the shadowy regions by first identifying the area of shadow, obtaining brightness information from a region near the shadow, where the brightness is optimal, applying statistical methods to determine the measured brightness as a regression function of the optimal brightness, and number and proximity of shadowy objects, then correcting the shadow area brightness by calculating the inverse of the function of the shadow brightness. With this method, the brightness within the shadowy or over brightness regions are corrected to appear at a substantially similar level of brightness as the region of optimal brightness in the image.

Abstract: A method of registering and vertically aligning multiply-layered images into a mosaic is described. The method comprises performing an iterative process of vertical alignment of layers into a mosaic using a series of defined alignment correspondence pairs and global registration of images in a layer using a series of defined registration correspondence points and then redefining the identified alignment correspondence pairs and/or registration correspondence points until a satisfactory result is obtained. Optionally, an initial global registration of each layer could be performed initially before commencing the alignment process. The quality of the result could be determined using a least squares error minimization or other technique.

Abstract: The present invention involves a computationally efficient method of determining the locations of standard cells in an image of an IC layout. The initial step extracts and characterizes points of interest of the image. A coarse localization of possible standard cell locations is performed and is based on a comparison of the points of interest of an instance of an extracted standard cell and the remaining points of interest in the image. A more rigid comparison is made on the list of possible locations comprising a coarse match and a fine match. The coarse match results in a shortlist of possible locations. The fine match performs comparisons between the template and the shortlist. Further filtering is done to remove the effects of noise and texture variations and statistics on the results are generated to achieve the locations of the standard cells on the IC layout.

Abstract: The present invention involves a computationally efficient method of determining the locations of standard cells in an image of an IC layout. The initial step extracts and characterizes points of interest of the image. A coarse localization of possible standard cell locations is performed and is based on a comparison of the points of interest of an instance of an extracted standard cell and the remaining points of interest in the image. A more rigid comparison is made on the list of possible locations comprising a coarse match and a fine match. The coarse match results in a shortlist of possible locations. The fine match performs comparisons between the template and the shortlist. Further filtering is done to remove the effects of noise and texture variations and statistics on the results are generated to achieve the locations of the standard cells on the IC layout.

Abstract: The present invention involves a computationally efficient method of determining the locations of standard cells in an image of an IC layout. The initial step extracts and characterizes points of interest of the image. A coarse localization of possible standard cell locations is performed and is based on a comparison of the points of interest of an instance of an extracted standard cell and the remaining points of interest in the image. A more rigid comparison is made on the list of possible locations comprising a coarse match and a fine match. The coarse match results in a shortlist of possible locations. The fine match performs comparisons between the template and the shortlist. Further filtering is done to remove the effects of noise and texture variations and statistics on the results are generated to achieve the locations of the standard cells on the IC layout.

Abstract: The present invention involves a computationally efficient method of determining the locations of standard cells in an image of an IC layout. The initial step extracts and characterizes points of interest of the image. A coarse localization of possible standard cell locations is performed and is based on a comparison of the points of interest of an instance of an extracted standard cell and the remaining points of interest in the image. A more rigid comparison is made on the list of possible locations comprising a coarse match and a fine match. The coarse match results in a shortlist of possible locations. The fine match performs comparisons between the template and the shortlist. Further filtering is done to remove the effects of noise and texture variations and statistics on the results are generated to achieve the locations of the standard cells on the IC layout.

Abstract: A method of registering and vertically aligning multiply-layered images into a mosaic is described. The method comprises performing an iterative process of vertical alignment of layers into a mosaic using a series of defined alignment correspondence pairs and global registration of images in a layer using a series of defined registration correspondence points and then redefining the identified alignment correspondence pairs and/or registration correspondence points until a satisfactory result is obtained. Optionally, an initial global registration of each layer could be performed initially before commencing the alignment process. The quality of the result could be determined using a least squares error minimization or other technique.

Abstract: A method and apparatus to reduce occurrences of electrically non-functional elements, known as dummy features, from a source data structure is described. The source data structure may be image data, a vector based data structure or some other data format. Dummy features in the source data structure are detected and then deleted. Dummy features may be detected by selecting a representative dummy feature, using it as a reference pattern or polygon and comparing it to features in the source data structure. The step of comparing the selected reference to the comprises selecting a cut-off correlation threshold value, and computing the correlation coefficients between the reference and the feature. Features are selectively removed based on a comparison between their correlation coefficients and the selected cut-off correlation threshold value. This threshold value may require updating to remove all dummy features in the source data structure.