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Journal ArticleDOI

Memetically Optimized MCWLD for Matching Sketches With Digital Face Images

TLDR
An automated algorithm to extract discriminating information from local regions of both sketches and digital face images is presented and yields better identification performance compared to existing face recognition algorithms and two commercial face recognition systems.
Abstract
One of the important cues in solving crimes and apprehending criminals is matching sketches with digital face images. This paper presents an automated algorithm to extract discriminating information from local regions of both sketches and digital face images. Structural information along with minute details present in local facial regions are encoded using multiscale circular Weber's local descriptor. Further, an evolutionary memetic optimization algorithm is proposed to assign optimal weight to every local facial region to boost the identification performance. Since forensic sketches or digital face images can be of poor quality, a preprocessing technique is used to enhance the quality of images and improve the identification performance. Comprehensive experimental evaluation on different sketch databases show that the proposed algorithm yields better identification performance compared to existing face recognition algorithms and two commercial face recognition systems.

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Citations
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Journal ArticleDOI

Graphical Representation for Heterogeneous Face Recognition

TL;DR: In this article, a graphical representation based HFR method (G-HFR) is proposed to represent heterogeneous image patches separately, which takes the spatial compatibility between neighboring image patches into consideration.
Book ChapterDOI

Heterogeneous Face Recognition with CNNs

TL;DR: Experimental results show that CNNs trained on visible spectrum images can be used to obtain results that are on par or improve over the state-of-the-art for heterogeneous recognition with near-infrared images and sketches.
Journal ArticleDOI

Multiple Representations-Based Face Sketch–Photo Synthesis

TL;DR: A novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch that combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches.
Journal ArticleDOI

A survey on heterogeneous face recognition

TL;DR: This survey provides a comprehensive review of established techniques and recent developments in HFR, and offers a detailed account of datasets and benchmarks commonly used for evaluation.
Journal ArticleDOI

Recognizing disguised faces: human and machine evaluation.

TL;DR: An automated algorithm is developed to verify the faces presented under disguise variations using automatically localized feature descriptors which can identify disguised face patches and account for this information to achieve improved matching accuracy.
References
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Book ChapterDOI

Lighting and pose robust face sketch synthesis

TL;DR: A robust algorithm for synthesizing a face sketch from a face photo taken under a different lighting condition and in a different pose than the training set is proposed using a multiscale Markov Random Field (MRF) model.
Proceedings ArticleDOI

A framework for recognizing a facial image from a police sketch

TL;DR: A theory and practical computations for automatically matching a police artist sketch to a set of true photographs and results using real police sketches and arrest photos are presented.
Proceedings ArticleDOI

On matching sketches with digital face images

TL;DR: In this article, a genetic optimization based approach is proposed to find the optimum weights corresponding to each facial region for matching, the information obtained from different levels of Laplacian pyramid are combined to improve the identification accuracy.
Journal ArticleDOI

Human Face Image Searching System Using Sketches

TL;DR: The concept of ldquohuman-in-the-looprdquo is used and a human face image searching algorithm using relevance feedback in the second phase is proposed and the results are encouraging.
Journal ArticleDOI

Hand-Drawn Face Sketch Recognition by Humans and a PCA-Based Algorithm for Forensic Applications

TL;DR: The performances of humans and a principle component analysis (PCA)-based algorithm in recognizing face sketches are compared and the algorithm was superior with the sketches of less distinctive features, while humans seemed more efficient in handling tonality (or pigmentation) cues of the sketches that were not processed with advanced transformation functions.
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