The task is to build an intelligent sensor that can instruct a Lego robot to perform certain tasks. The sensor is mounted on the Lego robot and it contains a digital camera which takes continuous images of the front view of the robot. These images are received by an FPGA which simultaneously saves them in an external storage device (SDRAM). At one time only one image is saved and during the time it is being saved, FPGA processes the image to extract some meaningful information. In front of digital camera there are different objects. The sensor is made to classify various objects on the basis of their color. For the classification, the requirement is to implement color image segmentation based object tracking algorithm on a small Field Programmable Gate array (FPGA). For the color segmentation in the images, we are using RGB values of the pixels and with the comparison of their relative values we get the binary image which is processed to determine the shape of the object. A histogram is used to retrieve object‟s features and saves results inside the memory of FPGA which can be read by an external microcontroller with the help of serial port (RS-232).

This thesis aims to present a color segmentation approach for traffic sign recognition based on LVQ neural networks. The RGB images were converted into HSV color space, and segmented using LVQ depending on the hue and saturation values of each pixel in the HSV color space. LVQ neural network was used to segment red, blue and yellow colors on the road and traffic signs to detect and recognize them. LVQ was effectively applied to 536 sampled images taken from different countries in different conditions with 89% accuracy and the execution time of each image among 31 images was calculated in between 0.726sec to 0.844sec. The method was tested in different environmental conditions and LVQ showed its capacity to reasonably segment color despite remarkable illumination differences. The results showed high robustness.

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Color plays a vitally important role in the world we live in. It surrounds us everywhere we go. Achromatic life, restricted to black, white and grey, is extremely dull. Color fascinates artists, for it adds enormously to aesthetic appreciation, directly invoking thoughts, emotions and feelings. Color fascinates scientists. For decades, scientists in color imaging, printing and digital photography have striven to satisfy increasing demands for accuracy in color reproduc- tion. Fluorescence is a very common phenomenon observed in many objects such as gems and corals, writing paper, clothes, and even laundry detergent. Traditional color imaging algo- rithms exclude fluorescence by assuming that all objects have only an ordinary reflective com- ponent. The first part of the thesis shows that the color appearance of an object with both reflective and fluorescent components can be represented as a linear combination of the two components. A linear model allows us to separate the two components using independent component analysis (ICA). We can then apply different algorithms to each component, and combine the results to form images with more accurate color. Displaying color images accurately is as important as reproducing color images accurately. The second part of the thesis presents a new, practical model for displaying color images on self-luminous displays such as LCD monitors. It shows that the model accounts for human visual system’s mixed adaptation condition and produces results comparable to many existing algorithms.

This study explored the phenomenon that a consumer's preference on color of car body may vary depending on shape of the car body. First, the study attempted to establish a theoretical framework that can account for this phenomenon. This framework is based on the (modern-) Darwinism approach to the so-called evolutionary psychology and aesthetics. It assumes that human's aesthetic sense works like an agent that seeks for environmental patterns that potentially afford to benefit the underlying needs of the agent, and this seeking process is evolutionary fitting. Second, by adopting the framework, a pattern called fundamental aesthetic dimensions was developed for identifying and modeling consumers aesthetic response to car body shape and color. Next, this study developed an effective tool that is capable in capturing and accommodating consumers color preference on a given car body shape. This tool was implemented by incorporating classic color theories and advanced digital technologies; it was named Color-Shape Synthesizer. Finally, an experiment was conducted to verify some of the theoretical developments. This study concluded (1) the fundamental aesthetics dimensions can be used for describing aesthetics in terms of shape and color; (2) the Color-Shape Synthesizer tool can be well applied in practicing car body designs; and (3) mapping between semantic representations of aesthetic response to the fundamental aesthetics dimensions can likely be a multiple-network structure.

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Aerial images had been used in various fields. If the shooting it in conditions of bad weather, that quality was damage. So requires use of image processing methods for improvement. With the growth and progress of technology, image enhancement method is quickly flourishing. That needs of different options for the appropriate treatment. In this study, image enhancement by the nature of Bi-dimensional empirical mode decomposition (BEMD). Empirical mode decomposition in nonlinear signal processing has excellent results. It can break out some of the base signal and trend. In the BEMD of the signal information for the edge of the image, the trend term for the light distribution. Decomposition can be retained the edge features of the image, and contrast of light and shadow maps make adjustments to improve the uneven lighting situations. In order to retain the color information, so the decomposition of the image before the image for color conversion, will be divided into three¡@degrees of brightness and color images, and then the brightness of the image for the¡@decomposition of the action. The use of subjective and objective image evaluation indicators, to determine the two-dimensional empirical mode decomposition¡@ method with other image enhancement difference. The results show that the conventional image enhancement has a problem that bright side of the whole image, resulting in reduced edge feature information. However, BEMD to effectively improve the image problem of uneven brightness and thoroughly to keep edge features.

OLEDs for display and lighting applications were studied. Both RGB and color filter technologies were discussed in the display section; meanwhile, RGB white light and tendem white light were discussed in the lighting section. A high performance RGB white display using 1,3,5-tri(1-pyrenyl) benzene (TPB3), C545T (166000 cd/m2) and DCJTB (70600 cd/m2) has been prepared with a 53.3% color gamut. For the color display using PLED technology, a glycerol modified PEDOT (G-PEDOT) is used as buffer layer material. Luminance of the white PLED display increases significantly from 11580 cd/m2 to 16040 cd/m2. A 54.5% color gamut color display is prepared using the white PLED device with a color filter. RGB white device with maximum luminance of 55800 cd/m2, maximum luminance efficiency of 4.55 cd/A, maximum power efficiency of 3.85 lm/W, and CIE coordinate of (0.33, 0.32) is prepared with a device structure of ITO(1300A)/NPB(500A)/TPB3(200A)/DPVBi¡G2% DSB(150A)/Alq3¡G2% DCJTB (150A)/ Alq3(350A)/LiF(8A)/Al(2000A). A high performance single emission layer white OLED device is also prepared. This single-layer device achieves a maximum luminance of 95200 cd/m2, maximum luminance efficiency of 5.9 cd/A, maximum power efficiency of 4.06 lm/W, and CIE coordinate of (0.34, 0.39) with a device structure of ITO(1300A)/NPB(650A)/TPB3:6% DSB:0.6% DCJTB(400A)/Alq3(300A)/LiF(8A)/Al(2000A). Optimization of a tandem OLED device is conducted using a Alq3¡GLi/ HAT-CN interlayer. It is found that turn-on voltage is reduced effectively using the Alq3¡GLi/ HAT-CN interlayer at 20 mA/cm2. Power efficiency is increased to 2.24 lm/W, and maximum luminance of 71790 cd/m2 is achieved with a CIE coordinate of (0.30, 0.39).