Call number: LD2668 .T4 1978 V58 / Master of Science

Call number: LD2668 .T4 1979 J67 / Master of Science

Lau Hang-yee. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 121-123). / Abstracts in English and Chinese. / Abstract in English --- p.i / Abstract in Chinese --- p.iii / List of Figures --- p.ix / List of Tables --- p.xiii / Chapter Chapter 1: --- Introduction --- p.1 / Chapter 1.1 --- Objective --- p.1 / Chapter 1.2 --- Definition ofixel-based Algorithm --- p.2 / Chapter 1.3 --- Definition of Region-based Algorithm --- p.3 / Chapter 1.4 --- Definition of Graph-based Algorithm --- p.5 / Chapter 1.5 --- Colour Spaces --- p.7 / Chapter 1.5.1 --- Basics of Colour Vision --- p.7 / Chapter 1.5.2 --- RGB Model --- p.7 / Chapter 1.5.3 --- HSV Model --- p.8 / Chapter 1.6 --- Organization of Thesis --- p.9 / Chapter Chapter 2: --- 2-Mean Clustering --- p.10 / Chapter 2.1 --- Algorithm --- p.11 / Chapter 2.2 --- Experiment Results --- p.14 / Chapter 2.2.1 --- Intensity Images --- p.14 / Chapter 2.2.2 --- Colour Images (Using RGB) --- p.15 / Chapter 2.2.3 --- Colour Image (Using Hue) --- p.19 / Chapter 2.3 --- Discussions --- p.21 / Chapter 2.3.1 --- Advantages --- p.23 / Chapter 2.3.2 --- Disadvantages --- p.24 / Chapter Chapter 3: --- Region Growing with Region Adjacency Graph --- p.25 / Chapter 3.1 --- Algorithm --- p.26 / Chapter 3.1.1 --- Region Growingrocess --- p.26 / Chapter 3.1.2 --- Region Adjacency Graph Growingrocess --- p.27 / Chapter 3.2 --- Experiment Results --- p.30 / Chapter 3.2.1 --- Intensity Images --- p.30 / Chapter 3.2.2 --- Colour Images (Using RGB) --- p.33 / Chapter 3.2.3 --- Colour Image (Using Hue) --- p.37 / Chapter 3.3 --- Discussions --- p.39 / Chapter 3.3.1 --- Advantages --- p.42 / Chapter 3.3.2 --- Disadvantages --- p.43 / Chapter Chapter 4: --- Normalized Cuts --- p.45 / Chapter 4.1 --- Formulation of the Generalized Eigenvaluesystem --- p.47 / Chapter 4.2 --- Algorithm --- p.52 / Chapter 4.3 --- Modification of NC --- p.54 / Chapter 4.4 --- Experiment Results --- p.55 / Chapter 4.4.1 --- Feature Images --- p.56 / Chapter 4.4.2 --- Intensity Images --- p.64 / Chapter 4.4.3 --- Colour Images --- p.66 / Chapter 4.5 --- Discussions --- p.70 / Chapter 4.5.1 --- Advantages --- p.70 / Chapter 4.5.2 --- Disadvantages --- p.71 / Chapter Chapter 5: --- ixel-Region-Graph Method --- p.72 / Chapter 5.1 --- Algorithm --- p.74 / Chapter 5.1.1 --- Step --- p.75 / Chapter 5.1.2 --- Step R --- p.76 / Chapter 5.1.3 --- Step G --- p.77 / Chapter 5.2 --- CompareRG Method with Other Methods --- p.80 / Chapter 5.3 --- Experiment Results --- p.82 / Chapter 5.3.1 --- Feature Image --- p.82 / Chapter 5.3.2 --- Real Images - Set 1 --- p.84 / Chapter 5.3.3 --- Real Images - Set 2 --- p.87 / Chapter 5.3.4 --- Real Images - Set 3 --- p.94 / Chapter 5.3.5 --- Real Images - Set 4 --- p.96 / Chapter 5.4 --- Discussion --- p.97 / Chapter 5.4.1 --- Advantages --- p.99 / Chapter 5.4.2 --- Disadvantages --- p.99 / Chapter 5.5 --- Image Graph --- p.100 / Chapter Chapter 6: --- Conclusion --- p.103 / Appendix I --- p.107 / Appendix II --- p.120 / References --- p.121

The optical density of human macular pigment was measured for 50 observers ranging in age from 10 to 90 years. The psychophysical method required adjusting the radiance of a 1°, monochromatic light (400–550 nm) to minimize flicker (15 Hz) when presented in counterphase with a 460 nm standard. This test stimulus was presented superimposed on a broad-band, short-wave background. Macular pigment density was determined by comparing sensitivity under these conditions for the fovea, where macular pigment is maximal, and 5° temporally. This difference spectrum, measured for 12 observers, matched Wyszecki and Stiles's standard density spectrum for macular pigment. To study variation in macular pigment density for a larger group of observers, measurements were made at only selected spectral points (460, 500 and 550 nm). The mean optical density at 460 nm for the complete sample of 50 subjects was 0.39. Substantial individual differences in density were found (ca. 0.10–0.80), but this variation was not systematically related to age.

A standardized color code is used to aid the driver in the prompt recognition of highway signs. At night, these signs are illuminated by various light sources including the headlights and other fixed light sources. These light sources may distort the appearance of the colors of the signs at night. The first objective of this study was to provide information about human capabilities with respect to the recognition of different colors under daytime and nighttime lighting. The second objective was to examine the effect of changing the specifications for highway colors from the Federal Highway Administration (FHWA) standards to the American National Standards (ANSI) safety color specifications. A laboratory experiment was conducted in which subjects named the perceived colors of retroreflective signs viewed under daytime and nighttime lighting. Forty subjects from four different age groups representing the driving population participated in the study. Three color samples (red, orange, and yellow) in three different grades (engineering grade, high intensity grade, and diamond grade), and two different color specifications (FHWA and ANSI) were used. Four different fixed light sources (clear mercury, coated mercury, coated metal halide, and high pressure sodium) were used for illuminating the signs. For the nighttime condition, two headlights were used (metal halide and tungsten halogen). Daytime lighting was simulated using a fluorescent D-65 light source. Response times as well as correct responses for naming the colors were collected for each subject. Significant differences were found for nighttime versus daytime viewing of the signing materials. In general, for nighttime viewing, red and orange colors were identified faster than yellow color samples. In most cases, FHWA colors were identified significantly more accurately and faster than the ANSI colors. The coated metal halide headlight performed better than the other fixed light sources. There was no significant difference found between the tungsten halogen and the metal halide headlights. / Graduation date: 1991

Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 75-81).

Thesis (Ph. D.)--University of California, San Diego, and San Diego State University, 2004. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 71-75).

Thesis (Ph. D.)--University of California, San Diego, 2003. / Vita. Includes bibliographical references (leaves 102-105).

Thesis (Ph. D.)--University of California, San Diego and San Diego State University, 2003. / Vita. Includes bibliographical references (leaves 182-208).