Crime Scene Shoeprint Retrieval Using Hybrid Features and Neighboring Images

Wu, Yao; Wang, Xin‐Nian; Zhang, Tao

doi:10.3390/info10020045

Cited by 12 publications

(3 citation statements)

References 29 publications

(85 reference statements)

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“…The method can achieve good performance on shoeprints with periodic patterns. Wang et al [72][73][74][75] divided a shoeprint image into two different regions and extracted features in these regions by using the Wavelet Fourier-Mellin transform. Experiments were conducted on a database containing 10,096 shoeprints, and the accuracy at the top 2% was about 96.6%.…”

Section: Regional Feature-based Methodsmentioning

confidence: 99%

Crime Scene Shoeprint Image Retrieval: A Review

Dong

Shi

et al. 2022

Electronics

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Shoeprints performs a vital role in forensic investigations. It has been an advanced research issue in forensic science. The main purpose of shoeprint image retrieval is to acquire a ranking list of shoeprint images in a database, according to their feature similarities to the query image. In this way, a shoeprint can not only be used as an exhibit for bringing criminal charges but also to provide a clue to a case. The goal of this work is to present an overview of the existing works conducted in shoeprint image retrieval. We detail the different phases of the shoeprint retrieval task and present a summary of the state-of-the-art methods. We analyzed the difficulties and problems in this field and discussed future work directions. This review may help neophytes become involved in research easily and quickly.

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Section: Regional Feature-based Methodsmentioning

confidence: 99%

Crime Scene Shoeprint Image Retrieval: A Review

Dong

Shi

et al. 2022

Electronics

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“…In that case, the ontology-based reasoning engine can automatically identify potential matches or discrepancies with existing records, thereby aiding investigators in drawing timely and accurate conclusions. This proactive role of the ontology extends the system's utility beyond mere data storage, making it an invaluable tool for both reactive and proactive investigative processes [91,92,95,96].…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

Spyropoulos,

Bratsas,

Makris

et al. 2023

Information

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Nowadays, more and more sciences are involved in strengthening the work of law enforcement authorities. Scientific documentation is evidence highly respected by the courts in administering justice. As the involvement of science in solving crimes increases, so does human subjectivism, which often leads to wrong conclusions and, consequently, to bad judgments. From the above arises the need to create a single information system that will be fed with scientific evidence such as fingerprints, genetic material, digital data, forensic photographs, information from the forensic report, etc., and also investigative data such as information from witnesses’ statements, the apology of the accused, etc., from various crime scenes that will be able, through formal reasoning procedure, to conclude possible perpetrators. The present study examines a proposal for developing an information system that can be a basis for creating a forensic ontology—a semantic representation of the crime scene—through descriptive logic in the owl semantic language. The Interoperability-Enhanced information system to be developed could assist law enforcement authorities in solving crimes. At the same time, it would promote closer cooperation between academia, civil society, and state institutions by fostering a culture of engagement for the common good.

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“…According to the scope of representation, shoeprint classification and retrieval methods may roughly fall into three categories: global features-based methods, region features-based methods, and interest point-based methods. Methods using the global features usually take into consideration the whole shoeprint for extracting features, for example, the moments invariant methods [3,4], frequency domain methods [5,6,7,8,9,10], and convolutional neural network-based method [11,12]. Methods using the region feature usually divide shoeprints into different regions and extract features from these regions, for example, the maximally stable extreme regions (MSER)-based methods [13,14], the periodic pattern-based methods [15], the compositional active basis model-based methods [16,17], and the sparse representation methods [18].…”

Section: Introductionmentioning

confidence: 99%

Multi-Layer Feature Based Shoeprint Verification Algorithm for Camera Sensor Images

Wang

Zhang

2019

Sensors

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As a kind of forensic evidence, shoeprints have been treated as important as fingerprint and DNA evidence in forensic investigations. Shoeprint verification is used to determine whether two shoeprints could, or could not, have been made by the same shoe. Successful shoeprint verification has tremendous evidentiary value, and the result can link a suspect to a crime, or even link crime scenes to each other. In forensic practice, shoeprint verification is manually performed by forensic experts; however, it is too dependent on experts’ experience. This is a meaningful and challenging problem, and there are few attempts to tackle it in the literatures. In this paper, we propose a multi-layer feature-based method to conduct shoeprint verification automatically. Firstly, we extracted multi-layer features; and then conducted multi-layer feature matching and calculated the total similarity score. Finally, we drew a verification conclusion according to the total similarity score. We conducted extensive experiments to evaluate the effectiveness of the proposed method on two shoeprint datasets. Experimental results showed that the proposed method achieved good performance with an equal error rate (EER) of 3.2% on the MUES-SV1KR2R dataset and an EER of 10.9% on the MUES-SV2HS2S dataset.

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Crime Scene Shoeprint Retrieval Using Hybrid Features and Neighboring Images

Cited by 12 publications

References 29 publications

Crime Scene Shoeprint Image Retrieval: A Review

Crime Scene Shoeprint Image Retrieval: A Review

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

Multi-Layer Feature Based Shoeprint Verification Algorithm for Camera Sensor Images

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