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Abstract. The study of yeast cell morphology requires consistent identification of cell cycle phases based on cell bud size. A computer-based image processing algorithm is designed to automatically classify microscopic images of yeast cells in a microfluidic channel environment. The images were enhanced to reduce background noise, and a robust segmentation algorithm is developed to extract geometrical features including compactness, axis ratio, and bud size. The features are then used for classification, and the accuracy of various machine-learning classifiers is compared. The linear support vector machine, distance-based classification, and k-nearest-neighbor algorithm were the classifiers used in this experiment. The performance of the system under various illumination and focusing conditions were also tested. The results suggest it is possible to automatically classify yeast cells based on their morphological characteristics with noisy and low-contrast images. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

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Abstract-This paper presents the design of a monocular vision based particle filter localization system for urban settings that uses aerial orthoimagery as the reference map. One of the design objectives is to provide a low cost method for outdoor localization using a single camera. This relaxes the need for global positioning system (GPS) which may experience degraded reliability in urban settings. The second objective is to study the achievable localization performance with the aforementioned resources. Image processing techniques are employed to create a feature map from an aerial image, and also to extract features from camera images to provide observations that are used by a particle filter for localization.

Abstract-This paper presents an approach to lane assignment for highway vehicles that increases traffic throughput while ensuring vehicles can exit successfully at their destinations. To enhance traffic safety and increase lane capacities, vehicles can be organized into platoons with the objective of maximizing the travel distance that platoons stay intact and then apply lane assignment to these platoons. The goal of this research is to form a distributed control strategy to select lanes for platoons using inter-vehicle communication. We evaluate the current platoon lane assignment strategy and compare its improvement over average vehicle travel time with the lane assignment for single vehicles reported in our previous work [1]. Simulation results show that while cooperate control for single vehicle lane assignment does lead to decreased vehicle travel times, the implementation of cooperative lane assignment for platooning vehicles leads to an even greater reduction.

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