How to Make a Query in Image Retrieval with Partial Information Extracted from Multiple Image Samples?

2021 ◽  
pp. 2154021
Author(s):  
Sheung Wai Chan ◽  
Yiu-Ming Cheung
Keyword(s):  
Image Retrieval ◽  
Partial Information ◽  
Promising Result ◽  
Point Of View ◽  
Criminal Investigation ◽  
Boolean Operations ◽  
Multiple Image ◽  
Cluster Label ◽  
Image Query ◽  
Query Sample

The existing image retrieval methods generally require at least one complete image as a query sample. From the practical point of view, a user may not have an image sample in hand for query. Instead, partial information from multiple image samples would be available. This paper therefore attempts to deal with this problem by presenting a novel framework that allows a user to make an image query composed of several partial information extracted from multiple image samples via Boolean operations (i.e. AND, OR and NOT). Based on the request from the query, a Descriptor Cluster Label Table (DCLT) is designed to efficiently find out the result of Boolean operations on partial information. Experiments show the promising result of the proposed framework on commodity query and criminal investigation, respectively, although it is essentially applicable to different scenarios as well by changing descriptors.

scholarly journals Developing a Multi-channel Beamformer by Enhancing Spatially Constrained ICA for Recovery of Correlated EEG Sources

2018 ◽  
Author(s):  
N Samadzadehaghdam ◽  
B MakkiAbadi ◽  
E Eqlimi ◽  
F Mohagheghian ◽  
H Khajehpoor ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Partial Information ◽  
Minimum Variance ◽  
Point Of View ◽  
The Body ◽  
Correlated Sources ◽  
Source Imaging ◽  
Neuron Populations ◽  
Eeg Data ◽  
Robust Beamformer

Background: Brain source imaging based on electroencephalogram (EEG) data aims to recover the neuron populations’ activity producing the scalp potentials. This procedure is known as the EEG inverse problem. Recently, beamformers have gained a lot of consideration in the EEG inverse problem.Objective: Beamformers lack acceptable performance in the case of correlated brain sources. These sources happen when some regions of the brain have simultaneous or correlated activities such as auditory stimulation or moving left and right extremities of the body at the same time. In this paper, we have developed a multichannel beamformer robust to correlated sources. Material and Methods: We have looked at the problem of brain source imaging and beamforming from a blind source separation point of view. We focused on the spatially constraint independent component analysis (scICA) algorithm, which generally benefits from the pre-known partial information of mixing matrix, and modified the steps of the algorithm in a way that makes it more robust to correlated sources. We called the modified scICA algorithm Multichannel ICA based EEG Beamformer (MIEB).Results: We evaluated the proposed algorithm on simulated EEG data and compared its performance quantitatively with three algorithms: scICA, linearly-constrained minimum-variance (LCMV) and Dual-Core beamformers; it is considered that the latter is specially designed to reconstruct correlated sources.Conclusion:The MIEB algorithm has much better performance in terms of normalized mean squared error in recovering the correlated/uncorrelated sources both in noise free and noisy synthetic EEG signals. Therefore, it could be used as a robust beamformer in recovering correlated brain sources. 

Intelligent Content-Based Dermoscopic Image Retrieval with Relevance Feedback for Computer-Aided Melanoma Diagnosis

2017 ◽  
Vol 10 (1) ◽  
pp. 85-108 ◽  
Author(s):  
Khadidja Belattar ◽  
Sihem Mostefai ◽  
Amer Draa
Keyword(s):  
Skin Lesion ◽  
Image Retrieval ◽  
Relevance Feedback ◽  
Query Image ◽  
Melanoma Diagnosis ◽  
Computer Aided ◽  
Histogram Intersection ◽  
Dermoscopic Image ◽  
Image Query ◽  
Aided Diagnosis

The use of Computer-Aided Diagnosis in dermatology raises the necessity of integrating Content-Based Image Retrieval (CBIR) technologies. The latter could be helpful to untrained users as a decision support system for skin lesion diagnosis. However, classical CBIR systems perform poorly due to semantic gap. To alleviate this problem, we propose in this paper an intelligent Content-Based Dermoscopic Image Retrieval (CBDIR) system with Relevance Feedback (RF) for melanoma diagnosis that exhibits: efficient and accurate image retrieval as well as visual features extraction that is independent of any specific diagnostic method. After submitting a query image, the proposed system uses linear kernel-based active SVM, combined with histogram intersection-based similarity measure to retrieve the K most similar skin lesion images. The dominant (melanoma, benign) class in this set will be identified as the image query diagnosis. Extensive experiments conducted on our system using a 1097 image database show that the proposed scheme is more effective than CBDIR without the assistance of RF.

Similarity Measure for Image Retrieval Based on Hausdorff Distance

2014 ◽  
Vol 635-637 ◽  
pp. 1039-1044 ◽  
Author(s):  
He Qun Qiang ◽  
Chun Hua Qian ◽  
Sheng Rong Gong
Keyword(s):  
Image Retrieval ◽  
Pattern Matching ◽  
Similarity Measure ◽  
Hausdorff Measure ◽  
Hausdorff Distance ◽  
Experimental Result ◽  
Feature Vectors ◽  
Image Query ◽  
Feature Values ◽  
Object Similarity

In general, it is difficult to segment accurately image regions or boundary contours and represent them by feature vectors for shape-based image query. Therefore, the object similarity is often computed by their boundaries. Hausdorff distance is nonlinear for computing distance, it can be used to measure the similarity between two patterns of points of edge images. Classical Hausdorff measure need to express image as a feature matrix firstly, then calculate feature values or feature vectors, so it is time-consuming. Otherwise, it is difficult for part pattern matching when shadow and noise existed. In this paper, an algorithm that use Hausdorff distance on the image boundaries to measure similarity is proposed. Experimental result has showed that the proposed algorithm is robust.

Electronic Investigation Technologies and Modern Format of Technical and Criminalistic Support for Criminal Cases Investigation

2021 ◽  
Author(s):  
G.V. Romanova ◽  
◽  
V.I. Romanov ◽  
Keyword(s):  
Information Technologies ◽  
Rapid Development ◽  
Continuous Process ◽  
Modern Society ◽  
Legal Regulation ◽  
Point Of View ◽  
Criminal Investigation ◽  
Criminal Proceedings ◽  
Criminal Cases ◽  
Processing And Storage

The article considers the main aspects of the electronic criminal investigation technologies application from the point of view of modern legislation of Russia and foreign countries. In modern society, there is a continuous process of improving the means of transmitting information, developing and implementing new technical devices for its processing and storage. The rapid development of science and technology inevitably leads to the desire to regulate the relations that arise in this area from a legal point of view. Meanwhile, in the Russian legal science, the information space is defined through the unity of its two components: the technical one, which includes the communication and communication infrastructure, and the social one – the community of Internet users. In this regard, the normative regulation of this area justifiably causes objective difficulties. The development of high technologies leads to the most frequent use of a relatively new form of technical and forensic support for the investigation of criminal cases in the process of criminal investigation. In the modern practice of investigation, the traces left by criminals on various media due to the expansion of digitalization processes are becoming more and more important every year. Timely, systematic development of legal regulation of the use of electronic information technologies is recognized as the most important condition for the successful digitalization of criminal proceedings. Understanding the need for the introduction of electronic technologies in the investigation of a criminal case from the point of view of the informational and technological nature is necessary, since the criminal process should not be an exception within the framework of a single international information policy, and its technological effectiveness should be dominant.

CORRUPTION IN THE PENAL SYSTEM: CRIMINOLOGICAL ASPECTS

2021 ◽  
pp. 71-75
Author(s):  
Сергей Андреевич Сивцов
Keyword(s):  
Criminal Justice ◽  
Criminal Justice System ◽  
Justice System ◽  
Preventive Measures ◽  
Point Of View ◽  
Broad Sense ◽  
Criminal Investigation ◽  
Penal System ◽  
Illegal Acts ◽  
Main Component

В статье рассматриваются коррупционные проявления в уголовно-исполнительной системе России с криминологической точки зрения, проведен анализ причин и условий совершения коррупционных преступлений и меры профилактики. Приводятся мнения ученых-юристов о понятии коррупции, которое рассматривается как в узком, так и в широком смысле слова. Автором утверждается, что коррупция в большей мере выступает как социальное и криминологическое, чем правовое явление, поэтому рассматривать ее в рамках конкретных совершенных преступлений неверно, необходимо анализировать совокупность противоправных деяний с учетом их особенностей, а также причины и условия их совершения. Автор отмечает, что пенитенциарная преступность делится на две категории: на общеуголовную преступность (преступления, совершаемые осужденными) и иную преступность, основной составляющей которой выступает коррупционная преступность в учреждениях и органах УИС. На основе изучения криминологических научных источников автор предлагает классифицировать факторы совершения коррупционных преступлений сотрудниками УИС: факторы, присущие всем коррупционным преступлениям; и факторы, присущие пенитенциарной коррупции. В представленной статье автором указывается на недостаточность антикоррупционных механизмов. Комплекс предпринимаемых мер противодействия коррупции необходимо совершенствовать и расширять. The article examines corruption manifestations in the Russian Penal System from a criminological point of view, analyzes the causes and conditions of corruption crimes and preventive measures. The opinions of legal scholars on the concept of corruption, the content of the concept of corruption are given, it is considered both in the narrow and in the broad sense of the word. The author argues that Corruption acts more as a social and criminological phenomenon than a legal one, therefore it is not correct to consider it within the framework of specific crimes committed, it is necessary to analyze the totality of illegal acts taking into account their characteristics, as well as the causes and conditions of their commission. The author notes that penitentiary crime is divided into two categories: crimes committed by convicts (ordinary crime) and other crime, the main component of which is corruption crime in institutions and bodies of the criminal justice system. Based on the study of criminological scientific sources, the author proposes to classify the factors of corruption crimes committed by the employees of the Criminal Investigation Department: factors inherent in all corruption crimes; and factors inherent in penitentiary corruption. In the presented article, the author points out the insufficiency of anti-corruption mechanisms. The range of anti-corruption measures taken needs to be improved and expanded.

scholarly journals Robberies and Some Features of the Methodology of Investigating Robberies

2018 ◽  
Vol 3 (4) ◽  
pp. 15
Author(s):  
Duraković Adnan
Keyword(s):  
Police Officers ◽  
Point Of View ◽  
Criminal Investigation ◽  
Criminal Offense ◽  
Bodily Injury ◽  
Criminal Offenses ◽  
Sense Of Security ◽  
Criminal Control ◽  
Technical Measures ◽  
Strategic Goal

Robberies are crimes that particularly negatively and significantly affect the subjective sense of security (but also objective) in society. Special significance of robberies is that they are often on the edge of murder or serious bodily injury. From the criminal law and criminal investigation point of view, robberies range from the so-called "simple" cases in terms of their discovery and clarification to the very serious armed raid on individuals, money transport, legal persons such as banks and other monetary institutions. The suppression of property crimes, especially the part which includes delicts that are carried out using coercion (force and / or threat) like robberies, can be successfully carried out by methods that could be called criminalistic methods. These methods represent a kind of criminalistic engineering - criminal investigation engineering. Criminalistic engineering is all about adjusting criminal investigation tactics, forensic and legal actions and measures to special features of criminal offenses. When carrying out criminal investigation, authorized police officers must constantly take care of the so-called operational criminalistic strategy that rises above the tactical processing of a particular criminal offense, and is aimed at the creation and implementation of a complex of operational-tactical and technical measures and actions with the strategic goal of combating criminality as a whole. This is reflected in the organizational structure of the police and also in the way of criminal control which implies permanent, continuous and systematic penetration and supervision of the so-called the "dark belt" of crime.

scholarly journals Shape and Geometric Features-based Semantic Image Retrieval Using Multi-class Support Vector Machine

2017 ◽  
Author(s):  
Zohair Malki
Keyword(s):  
Support Vector Machine ◽  
Image Retrieval ◽  
Zernike Moment ◽  
Support Vector ◽  
Geometric Features ◽  
Text And Image ◽  
Semantic Image Retrieval ◽  
Query Engine ◽  
Geometrical Features ◽  
Image Query

In this paper, a new approach to retrieve semantic images based on shape and geometric features of image in conjunction with multi-class support vector machine is proposed. Zernike moment as shape feature is to verify the invariance of objects for silhouette image. In addition, a set of geometrical features is to explore the objects shape using two features of rectangularity and circularity. Then the extracted features are normalized and employed for multi-class support vector machine either for learning or retrieving processes. The retrieving process relies on three main tasks which namely Query Engine, Matching Module and Ontology Manger, respectively. Query Engine is to build the input text or image query using SPARQL language. The matching module extracts the shape and geometric features of image’s objects and employ them to Ontology Manger which in turn inserts them in ontology knowledge base. Benchmark mammals have been conducted to empirically conclude the outcome of proposed approach. Our experiment on text and image retrieval yields efficient results to problematic phenomena than previously reported.

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