A Beginner’s Guide to Image Multi-Level Thresholding emphasizes various image thresholding methods that are necessary for image pre-processing and initial level enhancement. Explains basic concepts and the implementation of Image Multi-Level Thresholding (grayscale and RGB images) Presents a detailed evaluation in real-time application, including the need for heuristic algorithm, the choice of objective and threshold function, and the evaluation of the outcome Describes how the image thresholding acts as a pre-processing technique and how the region of interest in a medical image is enhanced with thresholding Illustrates integration of the thresholding technique with bio-inspired algorithms Includes current findings and future directions of image multi-level thresholding and its practical implementation Emphasizes the need for multi-level thresholding with suitable examples The book is aimed at graduate students and researchers in image processing, electronics engineering, computer sciences and engineering.
This book describes analytical models and estimation methods to enhance performance estimation of pipelined multiprocessor systems-on-chip (MPSoCs). A framework is introduced for both design-time and run-time optimizations. For design space exploration, several algorithms are presented to minimize the area footprint of a pipelined MPSoC under a latency or a throughput constraint. A novel adaptive pipelined MPSoC architecture is described, where idle processors are transitioned into low-power states at run-time to reduce energy consumption. Multi-mode pipelined MPSoCs are introduced, where multiple pipelined MPSoCs optimized separately are merged into a single pipelined MPSoC, enabling further reduction of the area footprint by sharing the processors and communication buffers. Readers will benefit from the authors’ combined use of analytical models, estimation methods and exploration algorithms and will be enabled to explore billions of design points in a few minutes.
A Beginner’s Guide to Image Multi-Level Thresholding emphasizes various image thresholding methods that are necessary for image pre-processing and initial level enhancement. Explains basic concepts and the implementation of Image Multi-Level Thresholding (grayscale and RGB images) Presents a detailed evaluation in real-time application, including the need for heuristic algorithm, the choice of objective and threshold function, and the evaluation of the outcome Describes how the image thresholding acts as a pre-processing technique and how the region of interest in a medical image is enhanced with thresholding Illustrates integration of the thresholding technique with bio-inspired algorithms Includes current findings and future directions of image multi-level thresholding and its practical implementation Emphasizes the need for multi-level thresholding with suitable examples The book is aimed at graduate students and researchers in image processing, electronics engineering, computer sciences and engineering.
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