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Color-based for tree yield fruits image counting
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Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit based on shape analysis is presented. Color and shape analysis was utilized to segment the images of different fruits like apple, pomegranate obtained under different lighting conditions. First the input sectional tree image was converted from RGB colour space into the colour space transform (i.e., YUV, YIQ, or YCbCr). The resultant image was then applied to the algorithm for fruit segmentation. After it is applied Morphological Operations which is enhanced image then execute Blob counting method which identify the object and count the number of it. Accuracy of this algorithm used in this thesis is 82.21% for images that have been scanned.

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Research In Science And Technology
Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
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Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

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Publication Date
Wed Jan 01 2020
Journal Name
Studies In Big Data
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
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Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

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Publication Date
Wed Dec 14 2011
Journal Name
Journal Of Madenat Alelem College
Histological structure of the Eye in Tree Frog Hyla arborea savignyi
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This research was conducted to study the histological structure of the eye in the tree frog (Hyla arborea savignyi) and showed that it is composed of the eyeball and the lens and optic nerve. Appeared eyeball is surrounded by three Tunica from the inside to the outside are Tunica Interna, Tunica vasculosa, Tunica fibrosa. The tunica interna consists of the retina that consists of 10 layers are from outer to inner pigment epithelial layer, rods and cones layer, external limiting membrane, outer nuclear layer, outer plexiform layer, inner nuclear layer, inner plexiform layer , ganglion cells layer , nerve fibers layer, internal limiting membrane .The vascular tunic or Uvea consists of the choroid, ciliary body , and iris . The fibrous coat co

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
DESIGN AND IMPLEMENTATION AN IRAQI CITIES DATABASE USING K-D TREE
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This research include design and implementation of an Iraqi cities database using spatial data structure for storing data in two or more dimension called k-d tree .The proposed system should allow records to be inserted, deleted and searched by name or coordinate. All the programming of the proposed system written using Delphi ver. 7 and performed on personal computer (Intel core i3).

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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Publication Date
Mon Jan 01 2024
Journal Name
Euphrates Journal Of Agricultural Science
Measuring of Antioxidant enzyme activity and some fruits quality characteristics in apple trees
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In this study, a factorial experiment was conducted using a Randomized Complete Block Design (RCBD) with three replicates to investigate the effects of silicon at four concentrations: 0, 2, 4, and 6 ml/L, designated as S0, S1, S2, and S3, respectively and a calcium-boron combination at three concentrations: 0, (0.5 g/L Ca-EDTA, + 10 mg/L B), and (1 g/L Ca-EDTA, + 20 mg/L B), designated as C0, C1, and C2, respectively. on the activity of antioxidant enzymes and some qualitative traits of fruits. The results indicated that the studied traits were significantly influenced by the factors. Silicon application notably increased enzyme activity, treatment S3 showed the highest activity levels for peroxidase (POD) and superoxide dismutase (SOD) rea

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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Computer Science And Mobile Computing
. Interpolative Absolute Block Truncation Coding for Image Compression
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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Spin-Image Descriptors for Text-Independent Speaker Recognition
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Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

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