Planar Shoeprint Segmentation Based on the Multiplicative Intrinsic Component Optimization

Guo, Tianli; Tang, Yunqi; Wei, Guo

doi:10.1109/icivc.2018.8492844

Cited by 2 publications

(3 citation statements)

References 4 publications

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“…An automatic shoeprint image retrieval system mainly consists of three phases: the shoeprint image preprocessing phase, the shoeprint image feature extraction phase and the corresponding feature similarity measurement and ranking score computation phase [19]. The preprocessing phase aims to separate shoeprints from complex backgrounds and to enhance image quality [20][21][22]. The feature extraction phase is used to extract discriminative features to represent the shoeprint images.…”

Section: Shoeprint Retrieval 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: Shoeprint Retrieval Methodsmentioning

confidence: 99%

Crime Scene Shoeprint Image Retrieval: A Review

Dong

Shi

et al. 2022

Electronics

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“…Tianli Guo et al, (2018) published article in which the authors have tried to generate the planar shoeprint segmentation based multiplicative intrinsic component optimization. According to the authors, it is a complex task to extract the shoeprint pattern accurately in forensic science.…”

Section: Review Of Literaturementioning

confidence: 99%

“…Therefore leading towards massive growth of data and also towards the development of unstructured data to retrieve such meaningful information from these voluminous data has become a challenging and therefore the latest technologies such as Big Data Technologies are helping to solve the issues to certain extent. In order to retrieve the data technologies like content based retrievals also developed and utilized in the literature [1] [2] [3][4] [5]. However content based retrievals could be effective where the content to be retrieved can be described or presented in the meaningful manner.…”

Section: Introductionmentioning

confidence: 99%

A Mechanism for Sketch Based Image Retrievals using Generalized Gamma Mixture Model (GGMM) and Relevance Feedback Mechanism

Prasad*,

Prasad

2020

IJRTE

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The exponential growth of multimedia technologies facilitated the ease of developing various images having different shapes and scales. With the advent of mobile technologies, these messages so generated are being transmitted across the globe in different formats for different purposes. With these advancements methodologies thus developed for identifying or expressing subjects (individuals) their views by means of sketches. These sketch based images have many advantages, in particular, these images can be well considered in situations where the narration and capturing becomes difficult. The present article underlines a mechanism to interpret the images and also addresses the retrieval of such sketch based images using Generalized Gamma Mixture Model. The relevance feedback mechanism is utilized to retrieve more relevant to sketch based images based on the query image. The efficiency of the proposed word is evaluated using metrics like precision, recall, error rate, and retrieval accuracy.

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Planar Shoeprint Segmentation Based on the Multiplicative Intrinsic Component Optimization

Cited by 2 publications

References 4 publications

Crime Scene Shoeprint Image Retrieval: A Review

Crime Scene Shoeprint Image Retrieval: A Review

A Mechanism for Sketch Based Image Retrievals using Generalized Gamma Mixture Model (GGMM) and Relevance Feedback Mechanism

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