Spelling suggestions: "subject:"image processing digital techniques"" "subject:"lmage processing digital techniques""
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Image-based illumination analysis and applications. / CUHK electronic theses & dissertations collectionJanuary 2010 (has links)
Applications using image-based illumination analysis are very limited in the current literature of computer graphics. However, there are potentially more applications based on such analysis and estimation. In this thesis, we show two applications in computer graphics that can be directly benefited from using such analysis and estimation: photo colorization and texture synthesis. / Illumination is a very common phenomenon. All the photographs that we casually take with cameras exhibit such phenomenon. Computer graphicists usually simulate the illumination cast on objects based on physical models. While directly rendering such effects has been intensively studied in the field of computer graphics, the inverse estimation of illumination contribution to each pixel in the digital photographs, which we call image-based illumination estimation, still remains a challenging problem. The lack of the underlying geometry as well as the light source and material properties usually makes such inverse estimation ill-posed and a very difficult problem to solve. / In this thesis, we target on such image-based illumination estimation problem. We will review the current state-of-the-art illumination estimation algorithms for solving intrinsic images, and demonstrate their benefits and drawbacks. While this is a fundamental research problem in the field of computer vision, we show that by decomposing the image into its intrinsic components, the reflectance and illumination, many graphical applications can potentially be explored and benefited. In the meantime, we will also introduce a new and novel algorithm to efficiently estimate the intrinsic components based on the statistics of the textured regions. The same algorithm can also be directly applied to non-textured regions in an image. / Texture synthesis is a very fundamental problem in computer graphics. Current texture synthesis method is difficult to automatically take into account the illumination and deformation during the synthesis. By exploring the statistics of the texture, we propose a very efficient algorithm to estimate both the illumination and deformation fields on textures. The color of the illuminant is also taken into account so that the recovered reflectance has consistent color. By decomposing the illumination and deformation fields, we show that many texture-based applications, such as the preparation of texture exemplars from real photographs, the natural replacement of textured regions, the relighting of objects, as well as the manipulation of geometries in natural images can be well achieved, with the success of texture synthesis guided by illumination and deformation. / Traditional example-based colorization of natural images usually suffers from illumination inconsistency. The color transfer from areas such as highlights and shadows may severely harm the colorization result. We propose to consider the illumination problem in colorization and perform colorization in an illumination-free domain. The decomposition of the intrinsic components from multiple example images, as well as the recombination and utilization of these intrinsic components in colorization, form the foundation of the proposed technique. Consistent colorization results are obtained even though the example images are from different lighting conditions and viewing directions. / Liu, Xiaopei. / Adviser: Wong Tien Tsin. / Source: Dissertation Abstracts International, Volume: 73-03, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 76-83). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.
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Analysis and design of coefficient restoration in image coding. / CUHK electronic theses & dissertations collectionJanuary 2000 (has links)
Tse Fu Wing. / "June 2000." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (p. 172-177). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.
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3D reconstruction of specular micro-surfaces in typical electronic manufacturing. / CUHK electronic theses & dissertations collectionJanuary 2006 (has links)
As the electronic industry advances rapidly, the dimensions of the semiconductor products keep on being shrunk and that leads to more stringent requirement on process control and quality assurance. In particular, area array packages like BGA, CSP, flip chips, wafer bumping and wafer-level packaging need to have the 3D quality of some micro-surfaces inspected accurately and efficiently. An example of the micro-surfaces is the solder bumps for direct die-to-die bonding, which are of size as small as 60 to 600 microns in diameter. However, the tiny size and often highly specular and textureless nature of the surfaces make the inspection difficult. In addition, the size of the inspection system is required to be small so as to minimize restraint, on the operation of the various moving parts involved in the manufacturing process. / Experimental results with image data of a variety of objects have positively demonstrated the feasibility of the proposed methodology. / In the mechanism the inspection speed is governed by the number of needed images which also equals the number of spatial shiftings of the grating. This thesis also addresses how the grating, as well as its spatial shifting, can be designed optimally for minimizing this image number for faster inspection speed. An optimal solution to shifting strategy optimization is proposed that is applicable to any pattern on the fringe grating. A design method is also introduced for optimal pattern design, which has higher efficiency than brute-force searching. To reduce image number furthermore, bit-pairing codification mechanism and color-encoded pattern are proposed and verified to be more efficient. / In this thesis, I propose a new methodology for reconstructing micro-surfaces in 3D. The mechanism is based upon the familiar concept of binary structured-light, projection, but adapted, for the purpose of greatly reducing the system size, from the traditional setup of an array of multiple light sources to one with a single light source. The mechanism consists of a single light source in combination with a binary grating for projecting a binary pattern onto the target surface, and of a camera for capturing image of the illuminated scene. By shifting the binary grating in space and in every drifting taking a separate image of the illuminated surface, each position on the illuminated surface will be attached with a string of binary code over the sequence of captured images. With a suitable design of the binary grating, the binary code string can be made unique for each bump surface position, allowing exact correspondence between the binary pattern and image data, and subsequently 3D determination through triangulation. With such a bright-or-dark world for each image position, the issues of image saturation, image noise, and textureless nature of the target surfaces are avoided. / Jun Cheng. / "June 2006." / Adviser: Ronald Chi-kit Chung. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6499. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 107-117). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.
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Deformation analysis and its application in image editing.January 2011 (has links)
Jiang, Lei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 68-75). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background and Motivation --- p.5 / Chapter 2.1 --- Foreshortening --- p.5 / Chapter 2.1.1 --- Vanishing Point --- p.6 / Chapter 2.1.2 --- Metric Rectification --- p.8 / Chapter 2.2 --- Content Aware Image Resizing --- p.11 / Chapter 2.3 --- Texture Deformation --- p.15 / Chapter 2.3.1 --- Shape from texture --- p.16 / Chapter 2.3.2 --- Shape from lattice --- p.18 / Chapter 3 --- Resizing on Facade --- p.21 / Chapter 3.1 --- Introduction --- p.21 / Chapter 3.2 --- Related Work --- p.23 / Chapter 3.3 --- Algorithm --- p.24 / Chapter 3.3.1 --- Facade Detection --- p.25 / Chapter 3.3.2 --- Facade Resizing --- p.32 / Chapter 3.4 --- Results --- p.34 / Chapter 4 --- Cell Texture Editing --- p.42 / Chapter 4.1 --- Introduction --- p.42 / Chapter 4.2 --- Related Work --- p.44 / Chapter 4.3 --- Our Approach --- p.46 / Chapter 4.3.1 --- Cell Detection --- p.47 / Chapter 4.3.2 --- Local Affine Estimation --- p.49 / Chapter 4.3.3 --- Affine Transformation Field --- p.52 / Chapter 4.4 --- Photo Editing Applications --- p.55 / Chapter 4.5 --- Discussion --- p.58 / Chapter 5 --- Conclusion --- p.65 / Bibliography --- p.67
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Hybrid FDMA/CDMA wireless ATM and subband image coding.January 1996 (has links)
by Yeung Chi Kit. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 89-91). / Chapter I --- Hybrid FDMA/CDMA Wireless ATM --- p.1 / Chapter 1 --- Introduction --- p.2 / Chapter 1.1 --- Motivation --- p.2 / Chapter 1.2 --- Thesis Organization (PART I) --- p.5 / Chapter 2 --- Fundamentals --- p.6 / Chapter 2.1 --- Spread Spectrum --- p.6 / Chapter 2.1.1 --- Direct Sequence (DS) CDMA --- p.6 / Chapter 2.1.2 --- Frequency Hopping (FH) CDMA --- p.8 / Chapter 2.1.3 --- Time Hopping (TH) CDMA --- p.8 / Chapter 2.1.4 --- MC-CDMA (Multicarrier-CDMA) --- p.9 / Chapter 2.2 --- Asynchronous Transfer Mode (ATM) --- p.10 / Chapter 3 --- System Model --- p.12 / Chapter 4 --- System Capacity --- p.16 / Chapter 4.0.1 --- One Homogeneous User Population --- p.16 / Chapter 4.0.2 --- Two Homogeneous User Populations --- p.18 / Chapter 5 --- Conclusion --- p.24 / Chapter II --- Subband Image Coding --- p.28 / Chapter 6 --- Introduction --- p.29 / Chapter 6.1 --- Motivation --- p.29 / Chapter 6.2 --- Thesis Organization (PART II) --- p.31 / Chapter 7 --- Fundamentals --- p.33 / Chapter 7.1 --- Image Fidelity Criteria --- p.33 / Chapter 7.1.1 --- Numerical (Quantitative) Measures --- p.34 / Chapter 7.1.2 --- Perceptual (Subjective) Measure --- p.34 / Chapter 8 --- Wavelet Transform --- p.36 / Chapter 8.1 --- Wavelet Theory --- p.37 / Chapter 8.2 --- Multiresolution Analysis --- p.39 / Chapter 8.3 --- Quality Criteria for Wavelets --- p.42 / Chapter 8.4 --- Criteria for filters...................´ب --- p.43 / Chapter 8.5 --- Orthogonal Discrete Wavelet Transform --- p.45 / Chapter 8.6 --- Biorthogonal Discrete Wavelet Transform --- p.47 / Chapter 8.7 --- Wavelet Packets Transform --- p.48 / Chapter 8.8 --- Appendix --- p.50 / Chapter 8.8.1 --- QMF & CQF --- p.50 / Chapter 8.8.2 --- Examples of Orthogonal Filters --- p.53 / Chapter 8.8.3 --- Examples of Biorthogonal Filters --- p.53 / Chapter 9 --- Transform Coding and Compression --- p.55 / Chapter 9.1 --- Transformation Techniques --- p.56 / Chapter 9.2 --- Quantization --- p.57 / Chapter 9.2.1 --- Scalar Quantization --- p.57 / Chapter 9.2.2 --- Llyod-Max Quantization --- p.59 / Chapter 9.2.3 --- Vector Quantization --- p.59 / Chapter 9.2.4 --- Successive Approximation Entropy-Coded Quantization --- p.60 / Chapter 9.3 --- Entropy Coding --- p.61 / Chapter 9.3.1 --- Huffman Coding --- p.61 / Chapter 9.3.2 --- Arithmetic Coding --- p.62 / Chapter 9.3.3 --- Dictionary Based Coding --- p.64 / Chapter 9.3.4 --- Run Length Coding --- p.65 / Chapter 9.3.5 --- Example --- p.65 / Chapter 10 --- Embedded Zerotree Algorithm --- p.69 / Chapter 10.1 --- Significance Map Encoding --- p.70 / Chapter 10.2 --- Successive Approximation Entropy Coded Quantization --- p.72 / Chapter 10.3 --- Example --- p.74 / Chapter 10.4 --- Comments on EZW --- p.77 / Chapter 11 --- Residue Coding Using Embedded Zerotree Algorithm --- p.79 / Chapter 11.1 --- Residue Coding --- p.80 / Chapter 11.2 --- Results --- p.81 / Chapter 12 --- Conclusion --- p.86
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Low frequency coefficient restoration for image coding.January 1997 (has links)
by Man-Ching Auyeung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 86-93). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Transform coding and the JPEG scheme --- p.2 / Chapter 1.2 --- Motivation --- p.5 / Chapter 1.3 --- Thesis outline --- p.6 / Chapter 2 --- MED and DC Coefficient Restoration scheme --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- MED and DC Coefficient Restoration scheme --- p.10 / Chapter 2.2.1 --- Definition --- p.10 / Chapter 2.2.2 --- Existing schemes --- p.11 / Chapter 2.3 --- DC Coefficient Restoration scheme using block selection scheme --- p.14 / Chapter 2.4 --- Joint optimization technique --- p.16 / Chapter 2.4.1 --- Lagrange multiplier method --- p.17 / Chapter 2.4.2 --- Algorithm description --- p.18 / Chapter 2.5 --- Experimental results --- p.20 / Chapter 2.6 --- Summary --- p.32 / Chapter 3 --- Low Frequency Walsh Transform Coefficient Restoration scheme --- p.34 / Chapter 3.1 --- Introduction --- p.34 / Chapter 3.2 --- Restoration of low frequency coefficient using Walsh transform --- p.35 / Chapter 3.3 --- Selection of quantization table optimized for Walsh transform --- p.37 / Chapter 3.3.1 --- Image model used --- p.39 / Chapter 3.3.2 --- Infinite uniform quantization --- p.40 / Chapter 3.3.3 --- Search for an optimized quantization matrix --- p.42 / Chapter 3.4 --- Walsh transform-based LFCR scheme --- p.44 / Chapter 3.5 --- Experimental results --- p.46 / Chapter 3.6 --- Summary --- p.56 / Chapter 4 --- Low Frequency DCT Coefficient Prediction --- p.57 / Chapter 4.1 --- Introduction --- p.57 / Chapter 4.2 --- Low Frequency Coefficient Prediction scheme with negligible side information --- p.58 / Chapter 4.2.1 --- Selection of threshold --- p.63 / Chapter 4.2.2 --- Representation of the AC component --- p.63 / Chapter 4.3 --- Experimental results --- p.67 / Chapter 4.4 --- Summary --- p.84 / Chapter 5 --- Conclusions --- p.86 / Appendix A --- p.89 / Bibliography --- p.90
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DC coefficient restoration for transform image coding.January 1996 (has links)
by Tse, Fu Wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 155-[63]). / Acknowledgment --- p.iii / Abstract --- p.iv / Contents --- p.vi / List of Tables --- p.x / List of Figures --- p.xii / Notations --- p.xvii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- DC coefficient restoration --- p.1 / Chapter 1.2 --- Model based image compression --- p.5 / Chapter 1.3 --- The minimum edge difference criterion and the existing estima- tion schemes --- p.7 / Chapter 1.3.1 --- Fundamental definitions --- p.8 / Chapter 1.3.2 --- The minimum edge difference criterion --- p.9 / Chapter 1.3.3 --- The existing estimation schemes --- p.10 / Chapter 1.4 --- Thesis outline --- p.14 / Chapter 2 --- A mathematical description of the DC coefficient restoration problem --- p.17 / Chapter 2.1 --- Introduction --- p.17 / Chapter 2.2 --- Mathematical formulation --- p.18 / Chapter 2.3 --- Properties of H --- p.22 / Chapter 2.4 --- Analysis of the DC coefficient restoration problem --- p.22 / Chapter 2.5 --- The MED criterion as an image model --- p.25 / Chapter 2.6 --- Summary --- p.27 / Chapter 3 --- The global estimation scheme --- p.29 / Chapter 3.1 --- Introduction --- p.29 / Chapter 3.2 --- the global estimation scheme --- p.30 / Chapter 3.3 --- Theory of successive over-relaxation --- p.34 / Chapter 3.3.1 --- Introduction --- p.34 / Chapter 3.3.2 --- Gauss-Seidel iteration --- p.35 / Chapter 3.3.3 --- Theory of successive over-relaxation --- p.38 / Chapter 3.3.4 --- Estimation of optimal relaxation parameter --- p.41 / Chapter 3.4 --- Using successive over-relaxation in the global estimation scheme --- p.43 / Chapter 3.5 --- Experiments --- p.48 / Chapter 3.6 --- Summary --- p.49 / Chapter 4 --- The block selection scheme --- p.52 / Chapter 4.1 --- Introduction --- p.52 / Chapter 4.2 --- Failure of the minimum edge difference criterion --- p.53 / Chapter 4.3 --- The block selection scheme --- p.55 / Chapter 4.4 --- Using successive over-relaxation with the block selection scheme --- p.57 / Chapter 4.5 --- Practical considerations --- p.58 / Chapter 4.6 --- Experiments --- p.60 / Chapter 4.7 --- Summary --- p.61 / Chapter 5 --- The edge selection scheme --- p.65 / Chapter 5.1 --- Introduction --- p.65 / Chapter 5.2 --- Edge information and the MED criterion --- p.66 / Chapter 5.3 --- Mathematical formulation --- p.70 / Chapter 5.4 --- Practical Considerations --- p.74 / Chapter 5.5 --- Experiments --- p.76 / Chapter 5.6 --- Discussion of edge selection scheme --- p.78 / Chapter 5.7 --- Summary --- p.79 / Chapter 6 --- Performance Analysis --- p.81 / Chapter 6.1 --- Introduction --- p.81 / Chapter 6.2 --- Mathematical derivations --- p.82 / Chapter 6.3 --- Simulation results --- p.92 / Chapter 6.4 --- Summary --- p.96 / Chapter 7 --- The DC coefficient restoration scheme with baseline JPEG --- p.97 / Chapter 7.1 --- Introduction --- p.97 / Chapter 7.2 --- General specifications --- p.97 / Chapter 7.3 --- Simulation results --- p.101 / Chapter 7.3.1 --- The global estimation scheme with the block selection scheme --- p.101 / Chapter 7.3.2 --- The global estimation scheme with the edge selection scheme --- p.113 / Chapter 7.3.3 --- Performance comparison at the same bit rate --- p.121 / Chapter 7.4 --- Computation overhead using the DC coefficient restoration scheme --- p.134 / Chapter 7.5 --- Summary --- p.134 / Chapter 8 --- Conclusions and Discussions --- p.136 / Chapter A --- Fundamental definitions --- p.144 / Chapter B --- Irreducibility by associated directed graph --- p.146 / Chapter B.1 --- Irreducibility and associated directed graph --- p.146 / Chapter B.2 --- Derivation of irreducibility --- p.147 / Chapter B.3 --- Multiple blocks selection --- p.149 / Chapter B.4 --- Irreducibility with edge selection --- p.151 / Chapter C --- Sample images --- p.153 / Bibliography --- p.155
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Image reconstruction with multisensors.January 1998 (has links)
by Wun-Cheung Tang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references. / Abstract also in Chinese. / Abstracts --- p.1 / Introduction --- p.3 / Toeplitz and Circulant Matrices --- p.3 / Conjugate Gradient Method --- p.6 / Cosine Transform Preconditioner --- p.7 / Regularization --- p.10 / Summary --- p.13 / Paper A --- p.19 / Paper B --- p.36
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Video text detection and extraction using temporal information.January 2003 (has links)
Luo Bo. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 55-60). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.vi / Table of Contents --- p.vii / List of Figures --- p.ix / List of Tables --- p.x / List of Abbreviations --- p.xi / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Text in Videos --- p.1 / Chapter 1.3 --- Related Work --- p.4 / Chapter 1.3.1 --- Connected Component Based Methods --- p.4 / Chapter 1.3.2 --- Texture Classification Based Methods --- p.5 / Chapter 1.3.3 --- Edge Detection Based Methods --- p.5 / Chapter 1.3.4 --- Multi-frame Enhancement --- p.7 / Chapter 1.4 --- Our Contribution --- p.9 / Chapter Chapter 2 --- Caption Segmentation --- p.10 / Chapter 2.1 --- Temporal Feature Vectors --- p.10 / Chapter 2.2 --- Principal Component Analysis --- p.14 / Chapter 2.3 --- PCA of Temporal Feature Vectors --- p.16 / Chapter Chapter 3 --- Caption (Dis)Appearance Detection --- p.20 / Chapter 3.1 --- Abstract Image Sequence --- p.20 / Chapter 3.2 --- Abstract Image Refinement --- p.23 / Chapter 3.2.1 --- Refinement One --- p.23 / Chapter 3.2.2 --- Refinement Two --- p.24 / Chapter 3.2.3 --- Discussions --- p.24 / Chapter 3.3 --- Detection of Caption (Dis)Appearance --- p.26 / Chapter Chapter 4 --- System Overview --- p.31 / Chapter 4.1 --- System Implementation --- p.31 / Chapter 4.2 --- Computation of the System --- p.35 / Chapter Chapter 5 --- Experiment Results and Performance Analysis --- p.36 / Chapter 5.1 --- The Gaussian Classifier --- p.36 / Chapter 5.2 --- Training Samples --- p.37 / Chapter 5.3 --- Testing Data --- p.38 / Chapter 5.4 --- Caption (Dis)appearance Detection --- p.38 / Chapter 5.5 --- Caption Segmentation --- p.43 / Chapter 5.6 --- Text Line Extraction --- p.45 / Chapter 5.7 --- Caption Recognition --- p.50 / Chapter Chapter 6 --- Summary --- p.53 / Bibliography --- p.55
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Generic signboard detection in image and video.January 2003 (has links)
by Shen Hua. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 67-71). / Abstracts in English and Chinese. / Abstract --- p.i / 摘要 --- p.iii / Acknowledgments --- p.v / Table of Contents --- p.vii / List of Figures --- p.ix / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Object Detection --- p.2 / Chapter 1.2 --- Signboard Detection --- p.3 / Chapter Chapter 2 --- System Overview --- p.5 / Chapter 2.1 --- What is the problem? --- p.5 / Chapter 2.2 --- Review of previous work --- p.6 / Chapter 2.3 --- System Outline --- p.8 / Chapter Chapter 3 --- Preprocessing --- p.10 / Chapter 3.1 --- Edge Detection --- p.11 / Chapter 3.1.1 --- Gradient-Based Method --- p.11 / Chapter 3.1.2 --- Laplacian of Gaussian --- p.14 / Chapter 3.1.3 --- Canny edge detection --- p.15 / Chapter 3.2 --- Corner Detection --- p.18 / Chapter Chapter 4 --- Finding Candidate Lines --- p.22 / Chapter 4.1 --- Hough Transform --- p.22 / Chapter 4.1.1 --- What is Hough Transform --- p.22 / Chapter 4.1.2 --- Parameter Space --- p.22 / Chapter 4.1.3 --- Accumulator Array --- p.24 / Chapter 4.2 --- Gradient-based Hough Transform --- p.25 / Chapter 4.2.1 --- Direction of Gradient --- p.26 / Chapter 4.2.2 --- Accumulator Array --- p.28 / Chapter 4.2.3 --- Peaks in the accumulator array --- p.30 / Chapter 4.2.4 --- Performance of Gradient-based Hough Transform --- p.32 / Chapter Chapter 5 --- Signboards Locating --- p.35 / Chapter 5.1 --- Line Verification --- p.35 / Chapter 5.1.1 --- Line Segmentation --- p.35 / Chapter 5.1.2 --- Density Checking --- p.37 / Chapter 5.2 --- Finding Close Circuits --- p.40 / Chapter 5.3 --- Remove Redundant Segments --- p.47 / Chapter Chapter 6 --- Post processing --- p.54 / Chapter Chapter 7 --- Experiments and Conclusion --- p.59 / Chapter 7.1 --- Experimental Results --- p.59 / Chapter 7.2 --- Conclusion --- p.66 / Bibliography --- p.67
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