Shape Recognition of Linear Construction Entities from Construction Site Images

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of Image Processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based shape recognition model is presented. This model was devised to enhance the recognition capabilities of our existing material based image retrieval model. The shape recognition model is based on clustering techniques, and specifically those related with material and object segmentation. The model detects the borders of each previously detected material depicted in the image, examines its linearity (length/width ratio) and detects its orientation (horizontal/vertical). The results emonstrate the suitability of this model for construction site image retrieval purposes and reveal the capability of existing clustering technologies to accurately identify the shape of a wealth of materials from construction site images.

Passively harmonically mode-locked vertical-external-cavity surface-emitting laser emitting 1.1 ps pulses at 147 GHz repetition rate

Coupled-cavity passive harmonic mode-locking of a quantum well based vertical-external-cavity surface-emitting laser has been demonstrated, yielding an output pulse train of 1.5 ps pulses at a repetition rate of 80 GHz and with an average power of 80 mW. Harmonic mode-locking results from coupling between the main laser cavity and a cavity formed within the substrate of the saturable absorber structure. Mode-locking on the second harmonic of the substrate cavity allows a train of 1.1 ps pulses to be generated at a repetition rate of 147 GHz with 40 mW average power. © 2010 American Institute of Physics.