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Automatic face recognition performance is affected due to the head rotations and tilt, lighting intensity and angle, facial expressions, aging and partial occlusion of face using Hats, scarves, glasses etc.In this paper, illumination normalization of face images is done by combining 2D Discrete Cosine Transform and Contrast Limited Adaptive Histogram Equalization. The proposed method selects certain percentage of DCT coefficients and rest is set to 0. Then, inverse DCT is applied which is followed by logarithm transform and CLAHE. Thesesteps create illumination invariant face image, termed as 'DCT CLAHE' image. The fisher face subspace method extracts features from 'DCT CLAHE' imageand features are matched with cosine similarity. The proposed method is tested in AR database and performance measures like recognition rate, Verification rate at 1% FAR and Equal Error Rate are computed. The experimental results shows high recognition rate in AR database.

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Availability of content over the web is increasing exponentially. The demand for content by users is also increasing rapidly. The problem of making the right content available to user at the right time will continue to be a crucial issue. As variety of contents are available and variety of users are involved, there is no single way of matching the availability versus need and deliver content instantly especially in a limited mobile environment. Hence a hybrid method is proposed in this paper by combining the different techniques such as caching, pre-fetching and cache sharing with noise reduction to improve the overall performance of mobile for optimal cache memory utilisation, efficient bandwidth utilization, network traffic reduction and latency reduction. Efficiency of mobile caching and pre-fetching is improved using Enhanced Bloom Filter technique and data is shared among cooperative users by establishing a voluntary hub. The unwanted contents in the web page can be considered as noise which is removed when storing the web pages in cache or pre-fetch area. The success of the proposed method greatly depends on the hit ratio of contents rendered locally rather than getting it from server. In order to reduce server hits, sharing the contents of cache and pre-fetch area amongst mobile users is effective. Whenever any user requires new content, even if it is not available in browser cache or local cache of that user, the content can be rendered from the cache or pre-fetch area of collaborative mobile users rather than hitting the server. This hybrid cooperative cache sharing and pre-fetching for accessing the required contents improve the overall performance and hit ratio than the existing methods.