An Image Data Mining with its Effective Local Binary Patterns (LBP) Detection and Extraction with Hierarchical Indexing- A Review Paper

Image recognition has been one of the most interesting and important research fields in the past two decades. The reasons come from the need of automatic recognitions and surveillance systems, the interest in visual system on Image recognition, and the design of -computer inter image, etc. These researches involve knowledge and researchers from disciplines such as neuroscience, psychology, computer vision, pattern recognition, image processing, and machine learning,etc. A bunch of papers have been published to overcome difference factors (such as illumination, expression, scale, pose, etc)and achieve better recognition rate, while there is still no robust technique against uncontrolled practical cases which may involve kinds of factors simultaneously. Most of the current Image recognition systems presume that Images are readily available for processing. However, in reality, we do not get images with just Images. We need a system, which will detect the Image in image, so that this detected Image can be given as input to Image recognition systems. The goal of a Image detection algorithm is to identify the location and scale of all the Images in image. The task of Image detection is so trivial for the brain, yet it still remains a challenging and difficult problem to enable a computer to do Image detection. This is because the image changes with respect to internal factors like facial expression, beard and mustache, glasses etc and it is also affected by external factors like scale, lightning conditions, contrast between Image and background and orientation of the Image.