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      Handbook of Research on Emergent Applications of Optimization Algorithms : 

      Automatic Mask Alignment for Optical Lithography Using GA- and PSO-Based Image Registration Technique

      monograph
      IGI Global

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          Abstract

          Mask Alignment is a very important part of modern day VLSI fabrication process. To replicate the desired structure on the mask to the wafer, it is necessary to have some degree of accurate mask alignment procedure. However, present day mask alignment process is operated by manual inspection and hence may produce significant human errors. The objective of this work is to develop a novel mask alignment procedure based on image registration technique which is independent of manual inspection. For this purpose only requirement is a standard webcam to capture the images of mask and wafer to be registered. It is well known that registration is a technique by which one object is aligned geometrically with respect to other. Present study shows that genetic algorithm/particle swarm optimization based mask registration technique produces satisfactory results in a reasonable time. First section of this work describes the registration technique of mask and wafer images in details and following this registration values second part is hardware implementation of mask alignment procedure.

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          Particle swarm optimization

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            A new optimizer using particle swarm theory

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              Mutual-information-based registration of medical images: a survey.

              An overview is presented of the medical image processing literature on mutual-information-based registration. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. Methods are classified according to the different aspects of mutual-information-based registration. The main division is in aspects of the methodology and of the application. The part on methodology describes choices made on facets such as preprocessing of images, gray value interpolation, optimization, adaptations to the mutual information measure, and different types of geometrical transformations. The part on applications is a reference of the literature available on different modalities, on interpatient registration and on different anatomical objects. Comparison studies including mutual information are also considered. The paper starts with a description of entropy and mutual information and it closes with a discussion on past achievements and some future challenges.
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                Author and book information

                Book Chapter
                2018
                : 637-655
                10.4018/978-1-5225-2990-3.ch027
                641f860f-4366-402f-902d-008a9ee97912
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