Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CNN infrastructure. Findings: The results acquired through the investigated CBIR system alongside the benchmarked results have clearly indicated that the suggested technique had the best performance with the overall accuracy at 88.29% as opposed to the other sets of data adopted in the experiments. The outstanding results indicate clearly that the suggested method was effective for all the sets of data. Improvements/Applications: As a result of this study, it was found the revealed that the multiple image representation was redundant for extraction accuracy, and the findings from the study indicated that automatically retrieved features are capable and reliable in generating accurate outcomes.
In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.
Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse
... Show MoreThe study the problem emerged in the inability of local companies to enter the field of active competition with other companies operating in the same economic sector due to the high cost of their products, hence, the companies that want to apply this technique can effectively compete in order to achieve those objectives.
So this study focused on the goal of reducing the cost of products by reducing the cost product to a minimum , as the study was based in its hypothesis on the ability of companies to application this technique which in turn leads to increased profits under conditions of normal working and the power available and their potential in improving the quality of its products, as well as the need for full coordina
... Show MoreIn this work, we are obviously interested in a general solution for the calculation of the image of a single bar in partially coherent illumination. The solution is based on the theory of Hopkins for the formation of images in optical instruments in which it was shown that for all practical cases, the illumination of the object may be considered as due to a self – luminous source placed at the exit pupil of the condenser , and the diffraction integral describing the intensity distribution in the image of a single bar – as an object with half – width (U0 = 8 ) and circular aperture geometry is viewed , which by suitable choice of the coherence parameters (S=0.25,1.0.4.0) can be fitted to the observed distribution in various types of mi
... Show MoreIn the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res
... Show MoreUsing the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
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