Reference number : GC-2017-Q1-00563, amendment number : , agreement type : G, recipient legal name : Ukwatta, Eranga (Carleton University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Plus Grants for Universities, program name french : Subvention d'engagement partenarial Plus pour les universités, program purpose english : The objective of this proposal is to develop a software tool consisting of a suite of image analysis techniques to_x000D_
help automate the detection of patents infringement related to circuitry in integrated circuits (ICs). Our_x000D_
proposed software will aid in automating the process of circuit extraction, where an IC is reverse engineered to_x000D_
determine the exact construction and design of its electronic circuitry. Circuit extraction is sometimes required_x000D_
to determine infringement of patent(s). The process of circuit extraction is performed by individually removing_x000D_
layers of circuitry of an IC, imaging the layers using a scanning electron microscope (SEM), and analysing_x000D_
SEM images of the IC layout to reconstruct the circuit schematics. One of the main bottlenecks in the existing_x000D_
approach is the accurate segmentation of the precise IC layout from SEM images, because minute errors in_x000D_
segmentation usually lead to significant errors in the reconstructed IC schematics. Image intensity_x000D_
threshold-based methods, such as the one used currently by TechInsights to segment the SEM images tends to_x000D_
perform poorly under image noise, requires tedious manual inspection and correction and consequently results_x000D_
in increased production costs. In the previous NSERC Engage project, we developed an image-analysis_x000D_
pipeline, which consisted of an image normalization method, two image filters and two image segmentation_x000D_
methods for wires and vertical interconnect accesses (VIAs). The preliminary results indicated that the_x000D_
segmentation results obtained using the developed pipeline, as compared to the methods currently used by_x000D_
TechInsights, provided more accurate segmentations of the IC layout. In this proposed NSERC Engage Plus_x000D_
project, we will expand the recently developed pipeline to address the following remaining challenges: 1)_x000D_
utilizing not only SEM images created using backscattered electrons, but also the ones created using secondary_x000D_
electrons; 2) requiring two separate algorithms for segmenting wires and VIAs lead to inferior results due to_x000D_
image artifacts; 3) choosing optimized parameters for a given SEM image dataset; and 4) the long_x000D_
computational time of the level set segmentation method. We will develop a multi-region segmentation method, program purpose french : The objective of this proposal is to develop a software tool consisting of a suite of image analysis techniques to_x000D_
help automate the detection of patents infringement related to circuitry in integrated circuits (ICs). Our_x000D_
proposed software will aid in automating the process of circuit extraction, where an IC is reverse engineered to_x000D_
determine the exact construction and design of its electronic circuitry. Circuit extraction is sometimes required_x000D_
to determine infringement of patent(s). The process of circuit extraction is performed by individually removing_x000D_
layers of circuitry of an IC, imaging the layers using a scanning electron microscope (SEM), and analysing_x000D_
SEM images of the IC layout to reconstruct the circuit schematics. One of the main bottlenecks in the existing_x000D_
approach is the accurate segmentation of the precise IC layout from SEM images, because minute errors in_x000D_
segmentation usually lead to significant errors in the reconstructed IC schematics. Image intensity_x000D_
threshold-based methods, such as the one used currently by TechInsights to segment the SEM images tends to_x000D_
perform poorly under image noise, requires tedious manual inspection and correction and consequently results_x000D_
in increased production costs. In the previous NSERC Engage project, we developed an image-analysis_x000D_
pipeline, which consisted of an image normalization method, two image filters and two image segmentation_x000D_
methods for wires and vertical interconnect accesses (VIAs). The preliminary results indicated that the_x000D_
segmentation results obtained using the developed pipeline, as compared to the methods currently used by_x000D_
TechInsights, provided more accurate segmentations of the IC layout. In this proposed NSERC Engage Plus_x000D_
project, we will expand the recently developed pipeline to address the following remaining challenges: 1)_x000D_
utilizing not only SEM images created using backscattered electrons, but also the ones created using secondary_x000D_
electrons; 2) requiring two separate algorithms for segmenting wires and VIAs lead to inferior results due to_x000D_
image artifacts; 3) choosing optimized parameters for a given SEM image dataset; and 4) the long_x000D_
computational time of the level set segmentation method. We will develop a multi-region segmentation method, agreement title english : Further Development and Evaluation of an Automated Image Analysis Pipeline for Semiconductor Circuit Reverse Engineering, agreement title french : Further Development and Evaluation of an Automated Image Analysis Pipeline for Semiconductor Circuit Reverse Engineering, agreement number : EGP2, agreement value : 12500.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2018-2019), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada