An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

International review of environmental assessment tools and databases

Existing widely known environmental assessment models, primarily those for Life Cycle Assessment of manufactured products and buildings, were reviewed to grasp their characteristics, since the past several years have seen a significant increase in interest and research activity in the development of building environmental assessment methods. Each method or tool was assessed under the headings of description, data requirement, end-use, assessment criteria (scale of assessment and scoring/ weighting system)and present status