This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and change its characteristic are solved through calculating invariant eigen range of the recursive resolution forms of all sub-images coefficient. These approaches employed here as multi-wavelet transform identifier with minimum Mahalanobis distance. All method recognition proposed in this paper are applied on different images. Different tables of image recognition resulted in accurate and fast.
Background: This review aimed at explaining different methods of canine retraction along the archwire. Methods: Searching for different methods of canine retraction using fixed orthodontic appliances was carried out using different databases, including PubMed Central, Science Direct, Wiley Online Library, the Cochrane Library, Textbooks, Google Scholar, Research Gate, and hand searching from 1930 till February 2022. Results: After excluding the duplicate articles, papers describing the methods of canine retraction along the archwires were included. The most commonly used methods are NiTi closed coil spring and elastic chain. Conclusions: Various methods of canine retraction along the archwires were explained in detail regarding their adv
... Show MoreBackground: This review aims to discuss various canine retraction techniques using frictionless mechanics. Methods: Between 1930 and February 2022, searches were conducted about various canine retraction techniques using fixed orthodontic appliances in various databases, including PubMed Central, Science Direct, Wiley Online Library, the Cochrane Library, Textbooks, Google Scholar, Research Gate, and manual searching. Results: After removing the duplicate articles, publications that described how to use archwires to perform canine retraction with the archwires were included. Conclusions: The pros and cons of various canine retraction techniques using archwires were thoroughly discussed. T-loop is the preferred spring of all because of it
... Show Morein this work the polymides were prepared as rthemally stable polymers by diffrent ways
Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key
... Show MoreDigital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.
First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .
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