This paper describes a vision based pedestrian detection and tracking system which is able to count people in very crowded situations like escalator entrances in underground stations. The proposed system uses motion to compute regions of interest and prediction of movements, extracts shape information from the video frames to detect individuals, and applies texture features to recognize people. A search strategy creates trajectories and new pedestrian hypotheses and then filters and combines those into accurate counting events. We show that counting accuracies up to 98 % can be achieved.

One of the most important monitoring tasks of tunnel inspection is the observation of cracks. This paper describes an approach for crack following using mid-resolution (2-5mm per pixel) images of the tunnel surface. A mosaic on the basis of the tunnel design surface is built from images taken with a mobile platform. On this image representing the unwrapped tunnel surface texture the starting points of each crack are found semiautomatically using a modified Hough transform. Crack following takes place on the basis of local line fitting and exhaustive search in both directions of the crack, taking into account several restrictions, rules and optimization criteria to find the correct crack trajectory. A practical implementation polygonizes the extracted cracks and feeds them into a tunnel inspection data base. The method is applicable to various types of background texture as expected in the tunnel environment.

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An image acquisition and processing algorithm for inspection of tire treads has been developed. The tire treads are flat strips of black rubber material used as the main component in retreading automobile tires. These treads have a complex molded design on one side (DESIGN SIDE) and a fiat surface on the other side (see Figure 1). The inspection of the Design Side of the tread is one of the key operations in the tread fabrication process impacting quality and consistency of the final product. Increasing production rates and rigorous quality control demands put forth a requirement for the automation of the inspection operation. The main objective of the automated inspection system is to provide on-line, 100% inspection of the product for specified types of potential defects. Additional system benefit will include full access to the real-time process-control data, which can be used as process feedback parameters and allow implementation of advanced process-control techniques. This paper will discuss development of the main optical inspection algorithms utilized in the system design. The algorithms described in this paper were tested in the laboratory prototype of the inspection system and will be implemented in the final production system.

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