scholarly journals The Use Of Color, Wavelet Coefficient and Texture Features

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Kridalaksana Harsa Awang ◽  
Agus Harjoko
Keyword(s):  
Wavelet Coefficient ◽  
Texture Features ◽  
Input Image ◽  
Color Histogram ◽  
Video Database ◽  
Query Image ◽  
Database Application ◽  
Similar Images ◽  
Selection Of

A Query-by-Image ability often required in many multimedia or video database application. In this case the system retrieves similar images found in the database whose features are the same as the features of the query image. The key performance is in the selection of a set of features used for characterizing images in the video database. In this research a method for searching images in a video database is developed. The method accepts an image as its input and find similar images in the database. Three features are selected to characterize images in the database : color histogram, wavelet coefficients and texture. The method is tested on video database consisting eleven videos represented in RGB dan YCbCr color models. It was found that the method found all query images as long as the quality of the input image is good.

scholarly journals A Content Based Approach to Medical X-Ray Image Retrieval using Texture Features

2014 ◽  
Vol 12 (7) ◽  
pp. 3742-3748 ◽  
Author(s):  
Sumathi Ganesan ◽  
T.S. Subashini
Keyword(s):  
Image Retrieval ◽  
Imaging Techniques ◽  
Texture Features ◽  
X Rays ◽  
Query Image ◽  
City Block ◽  
X Ray ◽  
Important Research Topic ◽  
Similar Images ◽  
The City

Of late, the amount of digital X-ray images that are produced in hospitals is increasing incredibly fast. Efficient storing, processing and retrieving of X-ray images have thus become an important research topic. With the exponential need that arises in the search for the clinically relevant and visually similar medical images over a vast database, the arena of digital imaging techniques is forced to provide a potential and path-breaking methodology in the midst of technical advancements so as to give the best match in accordance to the user’s query image. CBIR helps doctors to compare X-rays of their current patients with images from similar cases and they could also use these images as queries to find the similar entries in the X-ray database. This paper focuses on six different classes of X-ray images, viz. chest, skull, foot, spine, pelvic and palm for efficient image retrieval. Initially the various X-rays are automatically classified into the six-different classes using BPNN and SVM as classifiers and GLCM co-efficient as features for classification. Indexing is done to make the retrieval fast and retrieval of similar images is based on the city block distance.  

scholarly journals An Efficient Two-layer based Technique for Content-based Image Retrieval

2021 ◽  
Vol 5 (1) ◽  
pp. 28
Author(s):  
Fawzi Abdul Azeez Salih ◽  
Alan Anwer Abdulla
Keyword(s):  
Image Retrieval ◽  
Texture Features ◽  
Superior Performance ◽  
Content Based Image Retrieval ◽  
Discrete Wavelet ◽  
Color Spaces ◽  
Query Image ◽  
Current State ◽  
Similar Images ◽  
Different Color

The rapid advancement and exponential evolution in the multimedia applications raised the attentional research on content-based image retrieval (CBIR). The technique has a significant role for searching and finding similar images to the query image through extracting the visual features. In this paper, an approach of two layers of search has been developed which is known as two-layer based CBIR. The first layer is concerned with comparing the query image to all images in the dataset depending on extracting the local feature using bag of features (BoF) mechanism which leads to retrieve certain most similar images to the query image. In other words, first step aims to eliminate the most dissimilar images to the query image to reduce the range of search in the dataset of images. In the second layer, the query image is compared to the images obtained in the first layer based on extracting the (texture and color)-based features. The Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP) were used as texture features. However, for the color features, three different color spaces were used, namely RGB, HSV, and YCbCr. The color spaces are utilized by calculating the mean and entropy for each channel separately. Corel-1K was used for evaluating the proposed approach. The experimental results prove the superior performance of the proposed concept of two-layer over the current state-of-the-art techniques in terms of precision rate in which achieved 82.15% and 77.27% for the top-10 and top-20, respectively.

FINGERPRINT ENHANCEMENT USING WAVELET TRANSFORM COMBINED WITH GABOR FILTER

2004 ◽  
Vol 18 (08) ◽  
pp. 1391-1406 ◽  
Author(s):  
WEIPENG ZHANG ◽  
YUAN YAN TANG ◽  
XINGE YOU
Keyword(s):  
Wavelet Transform ◽  
Gabor Filter ◽  
Wavelet Coefficient ◽  
Input Image ◽  
Identification System ◽  
Gabor Filtering ◽  
Fingerprint Image ◽  
Fingerprint Enhancement ◽  
Novel Approach

The performance of automatic fingerprint identification system (AFIS) is heavily determined by the quality of the input image, thus an effective method to enhance the fingerprint image is essential in such a system. In this paper, we combine the filter-based method, which is mostly used nowadays with wavelet transform to achieve a more reliable and effective approach to fingerprint enhancement. This novel approach consists of five main steps, namely: (1) normalization, (2) decomposition, (3) wavelet coefficient adjustment, (4) Gabor filtering, and (5) reconstruction. Using this new method, a more clear fingerprint image can be obtained, which can distinctly improve the accuracy of the minutiae extraction module and finally achieve a better performance of the entire system. Experiments have been conducted in our study and positive experimental results have been received, which show that the proposed combined method is more effective and robust than other existing methods such as the filter-based and direct gray-level approaches.

scholarly journals Proposed a Content-Based Image Retrieval System Based on the Shape and Texture Features

2019 ◽  
Vol 8 (11) ◽  
pp. 2185-2192
Keyword(s):  
Image Retrieval ◽  
Texture Feature ◽  
Texture Features ◽  
Visual Image ◽  
Content Based Image Retrieval ◽  
Query Image ◽  
Feature Extraction Method ◽  
Image Retrieval System ◽  
Reference Images ◽  
Similar Images

In this paper, we proposed a fusion feature extraction method for content based image retrieval. The feature is extracted by focusing on the texture and shape features of the visual image by using the Local Binary Pattern (LBP – texture feature) and Edge Histogram Descriptor (EHD – shape feature). The SVD is used for decreasing the number of the feature vector of images. The Kd-tree is used for reducing the retrieval time. The input to this system is a query image and Database (the reference images) and the output is the top n most similar images for the query image. The proposed system is evaluated by using (precision and recall) to measure the retrieval effectiveness. The values of the recall are between [43% –93%] and the average recall is 64.3%. The values of precision are between [30%-100%] and the average is 72.86% for the entire system and for both databases

scholarly journals CONTENT BASED IMAGE RETRIEVAL

2013 ◽  
pp. 294-299
Author(s):  
HARSHADA ANAND KHUTWAD ◽  
RAVINDRA JINADATTA VAIDYA
Keyword(s):  
Image Retrieval ◽  
Wavelet Decomposition ◽  
Texture Features ◽  
Content Based Image Retrieval ◽  
Image Search ◽  
Query Image ◽  
Shape Information ◽  
Color Correlogram ◽  
Similar Images ◽  
The Given

Content Based Image Retrieval is an interesting and most emerging field in the area of ‘Image Search’, finding similar images for the given query image from the image database. Current approaches include the use of color, texture and shape information. Considering these features in individual, most of the retrievals are poor in results and sometimes we are getting some non relevant images for the given query image. So, this dissertation proposes a method in which combination of color and texture features of the image is used to improve the retrieval results in terms of its accuracy. For color, color histogram based color correlogram technique and for texture wavelet decomposition technique is used. Color and texture based image

An Efficient Image Retrieval Based on Fusion of Fast Features and Query Image Classification

2017 ◽  
Vol 4 (1) ◽  
pp. 19-37 ◽  
Author(s):  
Vibhav Prakash Singh ◽  
Subodh Srivastava ◽  
Rajeev Srivastava
Keyword(s):  
Image Retrieval ◽  
Image Classification ◽  
Texture Features ◽  
Research Area ◽  
Vital Role ◽  
Query Image ◽  
Similar Images ◽  
Multiclass Classifier

Content Based Image Retrieval (CBIR) is an emerging research area in computer vision, in which, we yield similar images as per the query content. For the implementation of CBIR system, feature extraction plays a vital role, where colour feature is quite remarkable. But, due to unevenly colored or achromatic surfaces, the role of texture is also important. In this paper, an efficient and fast CBIR system is proposed, which is based on a fusion of computationally light weighted colour and texture features; chromaticity moment, colour percentile, and local binary pattern (LBP). Using these features with multiclass classifier, the authors propose a supervised query image classification and retrieval model, which filters all irrelevant class images. Basically, this model categorizes and recovers the class of a query image based on its visual content, and this successful classification of image significantly enhances the performance and searching time of retrieval system. Descriptive experimental analysis on benchmark databases confirms the effectiveness of proposed retrieval framework.

scholarly journals Band Selection for Dehazing Algorithms Applied to Hyperspectral Images in the Visible Range

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5935
Author(s):  
Sol Fernández-Carvelo ◽  
Miguel Ángel Martínez-Domingo ◽  
Eva M. Valero ◽  
Javier Romero ◽  
Juan Luis Nieves ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Histogram Equalization ◽  
Input Image ◽  
Visible Range ◽  
Quality Metric ◽  
Rgb Images ◽  
Image Quality Metric ◽  
Bad Weather ◽  
Selection Of

Images captured under bad weather conditions (e.g., fog, haze, mist, dust, etc.), suffer from poor contrast and visibility, and color distortions. The severity of this degradation depends on the distance, the density of the atmospheric particles and the wavelength. We analyzed eight single image dehazing algorithms representative of different strategies and originally developed for RGB images, over a database of hazy spectral images in the visible range. We carried out a brute force search to find the optimum three wavelengths according to a new combined image quality metric. The optimal triplet of monochromatic bands depends on the dehazing algorithm used and, in most cases, the different bands are quite close to each other. According to our proposed combined metric, the best method is the artificial multiple exposure image fusion (AMEF). If all wavelengths within the range 450–720 nm are used to build a sRGB renderization of the imagaes, the two best-performing methods are AMEF and the contrast limited adaptive histogram equalization (CLAHE), with very similar quality of the dehazed images. Our results show that the performance of the algorithms critically depends on the signal balance and the information present in the three channels of the input image. The capture time can be considerably shortened, and the capture device simplified by using a triplet of bands instead of the full wavelength range for dehazing purposes, although the selection of the bands must be performed specifically for a given algorithm.

ON THE EXPERT’S RIGHT TO BE PRESENT AT LEGAL PROCEEDINGS

2016 ◽  
Vol 15 ◽  
pp. 163-171
Author(s):  
M. G. Shcherbakovskiy
Keyword(s):  
Initial Data ◽  
Legal Proceedings ◽  
Reliable Assessment ◽  
Data Acquiring ◽  
Selection Of

The article discusses the reasonsfor an expert to participate in legal proceedings. The gnoseological reason for that consists of the bad quality of materials subject to examination that renders the examination either completely impossible or compromises objective, reasoned and reliable assessment of the findings. The procedural reason consists ofa proscription for an expert to collect evidence himself or herself. The author investigates into the ways of how an expert can participate in legal proceedings. If the defense invites an expert to participate in the proceedings, then it is recommended that his or her involvement should be in the presence of attesting witnesses and recorded in the protocol. In the course of the legal proceedings an expert has the following tasks: adding initial data, acquiring new initial data, understanding the situation of the incident, acquiring new objects to be studied, including samples for examination. An expert’s participation in legal proceedings differs from the participation of a specialist or an examination on the scene of the incident. The author describes the tasks that an expert solves in the course of legal proceedings, the peculiarities ofan investigation experiment practices, the selection of samples for an examination, inspection, interrogation.

Implementasi Voip Server Berbasis IPV6 Dengan Raspberry PI

2019 ◽  
Vol 9 (01) ◽  
pp. 47-54
Author(s):  
Rabbai San Arif ◽  
Yuli Fitrisia ◽  
Agus Urip Ari Wibowo
Keyword(s):  
Internet Protocol ◽  
Wireless Transmission ◽  
Raspberry Pi ◽  
Test Results ◽  
Average Delay ◽  
Ipv6 Network ◽  
Ip Network ◽  
Selection Of ◽  
Better Than

Voice over Internet Protocol (VoIP) is a telecommunications technology that is able to pass the communication service in Internet Protocol networks so as to allow communicating between users in an IP network. However VoIP technology still has weakness in the Quality of Service (QoS). VOPI weaknesses is affected by the selection of the physical servers used. In this research, VoIP is configured on Linux operating system with Asterisk as VoIP application server and integrated on a Raspberry Pi by using wired and wireless network as the transmission medium. Because of depletion of IPv4 capacity that can be used on the network, it needs to be applied to VoIP system using the IPv6 network protocol with supports devices. The test results by using a wired transmission medium that has obtained are the average delay is 117.851 ms, jitter is 5.796 ms, packet loss is 0.38%, throughput is 962.861 kbps, 8.33% of CPU usage and 59.33% of memory usage. The analysis shows that the wired transmission media is better than the wireless transmission media and wireless-wired.

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