The mobile phone as a platform for assisting the independent living ...

egions. Examining images based on the colours they contain is one of the most widelyused techniques because it does not depend on image size or orientation. Coloursearches will usually involve comparing colour histograms, though this is not the onlytechnique in practice.Texture measures look for visual patterns in images and how they are spatially defined.Textures are represented by texels which are then placed into a number of sets,depending on how many textures are detected in the image. These sets not only definethe texture, but also where in the image the texture is located. Texture is a difficultconcept to represent. The identification of specific textures in an image is achievedprimarily by modelling texture as a two-dimensional gray level variation. The relativebrightness of pairs of pixels is computed such that degree of contrast, regularity,coarseness and directionality may be estimated.Shape does not refer to the shape of an image but to the shape of a particular region thatis being sought out. Shapes will often be determined first applying segmentation or edgedetection to an image. In some cases accurate shape detection will require humanintervention because methods like segmentation are very difficult to completelyautomate.In the proposed indoor localization system we used three off-the-shelve algorithms forimage retrieval. The first two algorithms retrieve similar images based on colour(AForge.NET framework [17] [20], Eye.Open image processing library [18] ), while thethird (Image Recognition project [19] ) combine image retrieval based on shape andcolour.5.2 Optical Character Recognition (OCR)OCR is a field of research in pattern recognition, artificial intelligence and machine vision[24] . Optical character recognition, usually abbreviated to OCR, is the mechanical orelectronic translation of images of handwritten, typewritten or printed text into machineeditabletext.Though academic research in the field continues, the focus on OCR has shifted toimplementation of proven techniques. Optical character recognition (using opticaltechniques such as mirrors and lenses) and digital character recognition (using scannersand computer algorithms) were originally considered separate fields. Because very fewapplications survive that use true optical techniques, the OCR term has now beenbroadened to include digital image processing as well.30