Note: Intro -- Contents -- 1 Machine Vision Solutions in Automotive Industry -- Abstract -- 1…Introduction -- 2…Machine Vision -- 2.1 Basics of Machine Vision System -- 2.2 Camera, Lens and Illumination -- 2.2.1 Camera -- 2.2.2 Lens -- 2.2.3 Illumination -- 2.2.4 3-D Imaging System -- 2.3 Software -- 2.4 Interface to Production Environment -- 2.5 Interface to Management Information System -- 3…Applications -- 3.1 Application: Inspection of Spline Gear -- 3.2 Application: Inspection and Control of Flywheel Press System -- 4…Other Applications -- 5…Conclusions -- References -- 2 Kinect Quality Enhancement for Triangular Mesh Reconstruction with a Medical Image Application -- Abstract -- 1…Introduction -- 2…Methods -- 2.1 System Overview -- 2.2 A Background and the Characteristics of Microsoft Kinect -- 3…A Comprehensive Kinect Calibration Method -- 3.1 Calibration of RGB/Depth Camera -- 3.2 Calibration of Depth Sensor -- 3.3 Mapping Between RGB and Depth Image -- 4…The Tri-States Segmentation -- 5…Triangular Mesh Reconstruction -- 5.1 Average Filter -- 5.2 Marching Cubes Algorithm -- 5.3 Area Calculation -- 6…Experimental Result -- 7…Conclusion -- References -- 3 A Matlab GUI Package for Comparing Data Clustering Algorithms -- Abstract -- 1…Introduction -- 2…Clustering Algorithms -- 2.1 k-Means -- 2.2 Fuzzy c-Means -- 2.3 Hierarchical Clustering -- 2.4 Multiobjective Clustering with Support Vector Machine -- 3…Cluster Validity Index -- 3.1 Internal Validity Index -- 3.1.1 J Index -- 3.1.2 Davis-Bouldin Index -- 3.1.3 Dunn Index -- 3.1.4 Xie-Beni Index -- 3.1.5 I Index -- 3.1.6 Silhouette Index -- 3.2 External Validity Index -- 3.2.1 Minkowski Index -- 3.2.2 Adjusted Rand Index -- 3.2.3 Percentage of Correctly Classified Pairs -- 4…Demonstration of Cluster Package -- 4.1 Initial Window -- 4.2 k-Means Window -- 4.3 Fuzzy c-Means Window. , 4.4 Hierarchical Clustering Window -- 4.5 MocSvm Clustering -- 4.6 Report Table i.e. Result window -- 4.7 All Cluster Running Window -- 5…Conclusion -- References -- 4 Multi Objective Line Symmetry Based Evolutionary Clustering Approach -- Abstract -- 1…Introduction -- 2…Proposed Symmetry Based Distances -- 3…Multiple Randomized Kd Trees Based Nearest Neighbor Search -- 4…Multi Objective Line Symmetry Based Genetic Clustering Approach -- 4.1 Chromosome Representation -- 4.2 Fitness Computation -- 4.3 Genetic Operators -- 4.3.1 Selection -- 4.3.2 Crossover -- 4.3.3 Mutation -- 4.4 Termination Criterion -- 5…Data Sets and Experimental Results -- 5.1 Artificial Data Sets -- 5.2 Real Data Sets -- 6…Conclusion -- References -- 5 An Efficient Method for Contrast Enhancement of Digital Mammographic Images -- Abstract -- 1…Introduction -- 2…MIAS Database -- 3…Proposed Method -- 4…Simulation Results and Discussions -- 5…Conclusions -- References -- 6 Simulation of Obstacle Detection and Speed Control for Autonomous Robotic Vehicle -- Abstract -- 1…Introduction -- 2…Obstacle Detection and Avoidance -- 2.1 Image Processing Based Obstacle Detection -- 2.1.1 Stereo Vision -- 2.1.2 Monocular Vision -- 2.2 Proposed Method for Obstacle Avoidance -- 2.3 Digital Image Processing -- 2.3.1 Basic Relationships Between Pixels -- 2.3.2 Neighbours of a Pixel -- 2.3.3 Connectivity Between Pixels -- 2.3.4 Adjacency Between Pixels -- 2.3.5 Region -- 2.4 Algorithm for Obstacle Detection -- 2.4.1 Thresholding and Region Growing based Image Segmentation -- 3…Pid Controller Based Speed Control of PMDC Motor -- 3.1 PID Controller Overview -- 3.1.1 Proportional -- 3.1.2 Integral -- 3.1.3 Differential (Derivative) -- 3.2 Motor Parameters -- 3.3 Experimental Calculation of Motor Parameters -- 3.3.1 Electric Resistance and Inductance of Armature -- 3.3.2 Electromotive Force Constant. , 3.3.3 Moment of Inertia -- 3.3.4 Damping Ratio of the Mechanical System -- 3.4 PMDC Motor Equations -- 3.5 Tuning of Discrete PID Controller -- 3.5.1 Simulation Result -- 3.5.2 Computed Parameters -- 4…Matlab Simulink Based Image Processing for Obstacle Detection -- 4.1 MATLAB Simulink Model -- 4.1.1 RGB to Gray-Scale Conversion -- 4.1.2 Thresholding -- 4.2 Simulation Results -- 5…Results -- 5.1 PID Controller Module -- 5.2 Video Processing Module -- 6…Conclusion -- References -- 7 A Review of Global Path Planning Algorithms for Planar Navigation of Autonomous Underwater Robots -- Abstract -- 1…Introduction -- 2…Global Path Planning Algorithms -- 2.1 Breadth First Search (BFS) Algorithm -- 2.2 Depth First Search (DFS) Algorithm -- 2.3 A* Algorithm -- 2.4 Dijkstra's Algorithm -- 2.5 Wall Following Algorithm -- 3…Results and Discussion -- 3.1 Path Planning Through Randomly Located Obstacles -- 3.2 Maze Solving: A Comparison -- 3.3 Maze Solving by Wall Following Algorithm -- 3.4 Breadth First Search (BFS) and Depth First Search (DFS): A Comparison -- 4…Conclusions and Future Work -- Acknowledgments -- References -- 8 Pseudo-Fractional Tap-Length Learning Based Applied Soft Computing for Structure Adaptation of LMS in High Noise Environment -- Abstract -- 1…Introduction -- 2…Problem Formulation -- 3…Existing Algorithms for Dynamic Tap-Length Selection -- 3.1 The Fractional Variable Tap-Length Learning Algorithm -- 4…The VT-VSLMS Algorithm -- 5…Dynamic Tap-Length Optimization -- 6…Proposed Pseudo-Fractional Tap-Length Optimization -- 7…Simulation Setup -- 8…Results and Discussion -- 9…Conclusion -- References -- 9 Medical Image Analysis Using Soft Computing Techniques -- Abstract -- 1…Introduction -- 2…Image Database -- 3…Methodology -- 3.1 Algorithms for Brain Image Segmentation -- 3.2 Algorithms for Retinal Image Classification. , 4…Experimental Results and Discussions -- 4.1 Result Analysis of Brain Image Segmentation -- 4.2 Result Analysis of Retinal Image Classification -- 5…Conclusion -- Acknowledgments -- References -- 10 Selection of Robotic Grippers Under MCDM Environment: An Optimized Trade Off Technique -- Abstract -- 1…Introduction -- 2…Literature Survey -- 3…Problem Formulation -- 4…MCDM Methodologies -- 4.1 Analytic Hierarchy Process -- 4.2 TOPSIS -- 4.3 VIKOR -- 5…Solution Using AHP -- 6…Solution Using TOPSIS Methodology -- 7…Solution Using VIKOR Methodology -- 8…Conclusion -- References -- 11 Numerical Study of Viscous Flow in the Hydraulic System of Electro Optical Tracking System -- Abstract -- 1…Introduction -- 1.1 Description of the Hydraulic Systems -- 1.1.1 Oil Reservoir -- 1.1.2 Gear Pump -- 1.1.3 Manifold Block -- 1.1.4 Valves -- 1.1.5 Hydraulic Rotary Actuators -- 1.1.6 Electrical Panel -- 1.2 Selection of Fluid -- 2…Problem Formulation -- 2.1 Mathematical Modeling of Flow -- 2.2 Finite Difference Method for Solving the EOTS Pipeline Axial Flow -- 2.3 Problem Solving -- 3…Numerical Results and Analysis -- 3.1 Axial Velocity Distribution of EOTS Pipeline Axial Flow Field -- 3.2 Relationship Curve Between Axial Velocity and Cross Sectional Length of EOTS Pipeline Flow -- 3.3 Relationship Curve Between Wall Shear Stress and Cross Sectional Width and Height -- 3.4 Computation of f Re -- 4…Conclusion -- Acknowledgments -- A.x(118). Appendix: A -- A.x(118). Appendix: B -- References -- 12 Comparison of Edge Detection Algorithm for Part Identification in a Vision Guided Robotic Assembly System -- Abstract -- 1…Introduction -- 2…Related Work -- 3…System Structure -- 4…Edge Detection -- 4.1 Sobel Operator -- 4.2 Robert's Cross Operator -- 4.3 Prewitt's Operator -- 4.4 Laplacian of Gaussian Operator -- 4.5 Canny's Edge Detection Algorithm. , 5…Region Growing Algorithm -- 6…Shape Descriptor -- 7…Results and Discussion -- 7.1 Result of Canny's Operator -- 7.2 Result of LOG Operator -- 7.3 Result of Prewitt Operator -- 7.4 Result of Sobel Operator -- 7.5 Result of Roberts Operator -- 7.6 Comparision of Results -- 8…Conclusions -- References.