E-commerce is a growing market for selling gods and digital images are often used to display the product. However, there is a problem when the color of the object does not match the reality. This can lead to a dissatisfaction of the customer and a return of the product. Returned goods causes a significant loss in revenue for the suppliers. One reason for untruthful rendering of colors in images is due to different temperatures, or colors, of the illumination sources lighting the scene and the object. This effect can be reduced by a method called white balance. In this thesis, an algorithm based on the technique in Hsu et al. was implemented for a more truthful rendering of images of clothes and toys used in e-commerce. The algorithm removes unwanted color casts induced in the image from two different illumination sources. The thesis also marks important details missing in aforementioned paper as well as some drawbacks of the proposed technique, such as high processing time.

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Zebrafish swimming behavior is used in a new, automated drug assay system as a biomarker to measure drug efficiency to prevent or restore hearing loss. This system records video of zebrafish larvae under infrared lighting using Raspberry Pi cameras and measures fish swimming behavior. This automated system significantly reduces the operator time required to process experiments in parallel. Multiple tanks, each consisting of sixteen experiments are operated in parallel. Once a set of experiments starts, all data transfer and processing operations are automatic. A web interface allows the operator to configure, monitor and control the experiments and review reports. Ethernet connects the various hardware components, allowing loose coupling of the distributed software used to schedule and run the experiments. The operator can configure the data processing to be done on the local computer or offloaded to a high-performance computer cluster to achieve even higher throughput. Computationally efficient image processing algorithms provided automated zebrafish detection and motion analysis. Quantitative assessment of error in the position and orientation of the detected fish uses manual data analysis by human observers as the reference. The system error in orientation and position is comparable to human inter-operator error.