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Sajad Farokhi

dblp:148/0406 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2Databases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 50% Image and video processing · 50%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image representation
blur invariants
0.212016
Recognition of Images Degraded by Gaussian Blur · IEEE Trans. Image Process. 2016
Multimedia analysis and retrieval › object recognition
blur-invariant recognition
0.212016
Recognition of Images Degraded by Gaussian Blur · IEEE Trans. Image Process. 2016
Image and video processing › image representation
moment computation
0.212016
Recognition of Images Degraded by Gaussian Blur · IEEE Trans. Image Process. 2016
Multimedia analysis and retrieval
object recognition
0.212016
Recognition of Images Degraded by Gaussian Blur · IEEE Trans. Image Process. 2016

Methods — techniques the papers use, named apart from their topics

spectral domain projection · 0.2recursive moment computation · 0.2
YearPublicationVenuePosition
2016 Recognition of Images Degraded by Gaussian Blur
abstract
In this paper, we propose a new theory of invariants to Gaussian blur. We introduce a notion of a primordial image as a canonical form of all Gaussian blur-equivalent images. The primordial image is defined in spectral domain by means of projection operators. We prove that the moments of the primordial image are invariant to Gaussian blur and we derive recursive formulas for their direct computation without actually constructing the primordial image itself. We show how to extend their invariance also to image rotation. The application of these invariants is in blur-invariant image comparison and recognition. In the experimental part, we perform an exhaustive comparison with two main competitors: 1) the Zhang distance and 2) the local phase quantization.
Jan Flusser, Sajad Farokhi, Cyril Höschl IV, Tomás Suk, Barbara Zitová, Matteo Pedone
IEEE Trans. Image Process.2
2015 Recognition of Images Degraded by Gaussian Blur
Jan Flusser, Tomás Suk, Sajad Farokhi, Cyril Höschl IV
CAIP (1)3
2015 Near infrared face recognition using Zernike moments and Hermite kernels
Sajad Farokhi, Usman Ullah Sheikh, Jan Flusser
Inf. Sci.1