In this paper, we present a new sliding window based local thresholding technique ‘NICK’ and give a detailed comparison of some existing sliding-window based thresholding algorithms with our method. The proposed method aims at achieving better binarization results, specifically, for ancient document images. NICK has been inspired from the Niblack’s binarization method and exhibits its robustnes...

The SOVA and the log-MAP are commonly used in turbo decoding. In this paper, we propose to modify the sliding window MAP-algorithm in [5] to reduce the computational delay even further. We compare the simulation performance of this low latency log-MAP algorithm with the sliding window log-MAP. We also estimate the VLSI implementation complexities of the SOVA, the log-MAP and the proposed low la...

Figure 2. a) The phantom used in the simulations. b), c), and d) Plots comparing the sliding window techniques to an ideal sequence of images for three scenarios: b.) the pixel intensity increased and decreased, c.) the pixel intensity remained fixed while the phantom expanded and contracted, and d) the pixel intensity was conserved while the circle expanded and contracted. b) c) Reducing artif...

An automatic human cell detection system is proposed in this article. Histograms of Oriented Gradients are used for cell feature extraction. A robust search procedure, using variable sized sliding windows, is performed for cell localization in grayscale images. The proposed sliding-window based search algorithm is used in combination with a non-linear SVM-based feature vector classification tec...

Mining frequent patterns over data streams is an interesting problem due to its wide application area. In this study, a novel method for sliding window frequent patterns mining over data streams is proposed. This method utilizes a compressed and memory efficient tree data structure to store and to maintain sliding window transactions. The method dynamically reconstructs and compresses tree data...

Recently, the data stream, which is an unbounded sequence of data elements generated at a rapid rate, provides a dynamic environment for collecting data sources. It is likely that the embedded knowledge in a data stream will change quickly as time goes by. Therefore, catching the recent trend of data is an important issue when mining frequent itemsets from data streams. Although the sliding win...

In cognitive radio based cooperative sensing systems, some secondary users are likely to act malicious. Such secondary users are called malicious users. An optimal application of Dixon's outlier detection scheme for detecting malicious users in a cognitive radio cooperative spectrum sensing system has recently been termed as the Sliding Window Dixon's test. The Sliding window Dixon's test appli...

Counting the number of distinct elements in a data stream (distinct counting) is a fundamental aggregation task in database query processing, query optimization, and network monitoring. On a stream of elements, it is commonly needed to compute an aggregate over only the most recent elements, leading to the problem of distinct counting over a “sliding window” of the stream. We present a detailed...

A popular method of bounding the memory requirements of queries over data streamsis to use a sliding window, where old data are continuously removed as new data arrive.One problem that has not been addressed previously concerns indexing the results of slidingwindow queries. This is a noteworthy problem because data stream systems often materializecommon sub-expressions or final ...

This paper presents application of parametric techniques (Estimation of signal parameter by rotational invariance techniques (ESPRIT), Root multiple signal classification (Root MUSIC)) for the estimation of harmonics/inter harmonics produced by wind generator under constant, variable rotor speed, load imbalance. Accuracy of estimation by parametric techniques is checked on synthetic signal as w...