The Fractional Fourier transform (FrFT), as a generalization of the classical Fourier transform, was introduced many years ago in mathematics literature. For the enhanced computation of fractional Fourier transform, discrete version of FrFT came into existence i.e. DFrFT. This paper illustrates the advantage of discrete fractional Fourier transform (DFrFT) as compared to other transforms for steganography in image processing. The simulation result shows same PSNR in both domain (time and frequency) but DFrFT gives an advantage of additional stego key i.e. order parameter of this transform.
Ranking is a technique to categorize & finding the best option in the market. When number of bestoption is available in the market so its difficult to getting the best option is always a problem. In this paper we proposed a technique to optimize the ranking and its availability to check performance factor in order to maintained high ranking and quality of popular option in the market. We enhanced the line-up algorithm for ranking optimization approached, so, we used to line-up technique is demonstration to check other factor which affect to ranking of products, we are finding research to get factor detail which to improve the ranking of product.
In this paper, we present various classification methods for printedoptical character identification (POCR) similarly handwritten optical character identification (HOCR). Observation response of various method illustrate that which scheme produce batter recognition trueness in printed optical character identification (POCR) similarly handwritten optical character identification(HOCR). This article illustrate analysis of previous paper, and also distinguish the most important once out of the diversity of superior existing classification and feature extraction techniques and we will standardize the techniques by their feature circumstances and dataset used by different authors. It bring us to the performance of the algorithms produced to the expected efficiency.Feature withdrawal supporting to examine the shape controlled in the outline. While a quantity of feature taking out and categorization techniques are accessible, other than the picking of an exceptionallysuperior; technique decides the high degree of recognition correctness. A batch of author present investigation in this field and designnovel techniques of extraction and categorization. The corepurpose of this proposed article is to re-examine these techniques, so that the group of these techniques can be comprehended.
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