26 citations · 102 across the 15 of their papers we have counts for
20 papers
Unfolder: Fast localization and image rectification of a document with a crease from folding in half
A. M. Ershov, D. V. Tropin, E. E. Limonova +2
Presentation of folded documents is not an uncommon case in modern society. Digitizing such documents by capturing them with a smartphone camera can be tricky since a crease can di…
Fast matrix multiplication for binary and ternary CNNs on ARM CPU
Anton Trusov, Elena Limonova, Dmitry Nikolaev +1
Low-bit quantized neural networks are of great interest in practical applications because they significantly reduce the consumption of both memory and computational resources. Bina…
On the properties of some low-parameter models for color reproduction in terms of spectrum transformations and coverage of a color triangle
Alexey Kroshnin, Viacheslav Vasilev, Egor Ershov +3
One of the classical approaches to solving color reproduction problems, such as color adaptation or color space transform, is the use of low-parameter spectral models. The strength…
Advanced Hough-based method for on-device document localization
D. V. Tropin, A. M. Ershov, D. P. Nikolaev +1
The demand for on-device document recognition systems increases in conjunction with the emergence of more strict privacy and security requirements. In such systems, there is no dat…
ProLab: perceptually uniform projective colour coordinate system
Ivan A. Konovalenko, Anna A. Smagina, Dmitry P. Nikolaev +1
In this work, we propose proLab: a new colour coordinate system derived as a 3D projective transformation of CIE XYZ. We show that proLab is far ahead of the widely used CIELAB coo…
Illumination Estimation Challenge: experience of past two years
Egor Ershov, Alex Savchik, Ilya Semenkov +15
Illumination estimation is the essential step of computational color constancy, one of the core parts of various image processing pipelines of modern digital cameras. Having an acc…
ResNet-like Architecture with Low Hardware Requirements
Elena Limonova, Daniil Alfonso, Dmitry Nikolaev +1
One of the most computationally intensive parts in modern recognition systems is an inference of deep neural networks that are used for image classification, segmentation, enhancem…
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices
Anton Trusov, Elena Limonova, Dmitry Slugin +2
Quantized low-precision neural networks are very popular because they require less computational resources for inference and can provide high performance, which is vital for real-t…
Line detection via a lightweight CNN with a Hough Layer
Lev Teplyakov, Kirill Kaymakov, Evgeny Shvets +1
Line detection is an important computer vision task traditionally solved by Hough Transform. With the advance of deep learning, however, trainable approaches to line detection beca…
Approach for Document Detection by Contours and Contrasts
Daniil V. Tropin, Sergey A. Ilyuhin, Dmitry P. Nikolaev +1
This paper considers arbitrary document detection performed on a mobile device. The classical contour-based approach often fails in cases featuring occlusion, complex background, o…
Accelerated FBP for computed tomography image reconstruction
Anastasiya Dolmatova, Marina Chukalina, Dmitry Nikolaev
Filtered back projection (FBP) is a commonly used technique in tomographic image reconstruction demonstrating acceptable quality. The classical direct implementations of this algor…
Fast Implementation of Morphological Filtering Using ARM NEON Extension
Elena Limonova, Arseny Terekhin, Dmitry Nikolaev +1
In this paper we consider speedup potential of morphological image filtering on ARM processors. Morphological operations are widely used in image analysis and recognition and their…
Computational optimization of convolutional neural networks using separated filters architecture
Elena Limonova, Alexander Sheshkus, Dmitry Nikolaev
This paper considers a convolutional neural network transformation that reduces computation complexity and thus speedups neural network processing. Usage of convolutional neural ne…
Vanishing Point Detection with Direct and Transposed Fast Hough Transform inside the neural network
A. Sheshkus, A. Chirvonaya, D. Matveev +2
In this paper, we suggest a new neural network architecture for vanishing point detection in images. The key element is the use of the direct and transposed Fast Hough Transforms s…
A Document Skew Detection Method Using Fast Hough Transform
Pavel Bezmaternykh, Dmitry Nikolaev
The majority of document image analysis systems use a document skew detection algorithm to simplify all its further processing stages. A huge amount of such algorithms based on Hou…
A Method of Detecting End-To-End Curves of Limited Curvature
Ekaterina Panfilova, Mikhail Aliev, Irina Kunina +2
In this paper we consider a method for detecting end-to-end curves of limited curvature like the k-link polylines with bending angle between adjacent segments in a given range. The…
Bipolar Morphological Neural Networks: Convolution Without Multiplication
Elena Limonova, Daniil Matveev, Dmitry Nikolaev +1
In the paper we introduce a novel bipolar morphological neuron and bipolar morphological layer models. The models use only such operations as addition, subtraction and maximum insi…
HoughNet: neural network architecture for vanishing points detection
Alexander Sheshkus, Anastasia Ingacheva, Vladimir Arlazarov +1
In this paper we introduce a novel neural network architecture based on Fast Hough Transform layer. The layer of this type allows our neural network to accumulate features from lin…
Linear colour segmentation revisited
Anna Smagina, Valentina Bozhkova, Sergey Gladilin +1
In this work we discuss the known algorithms for linear colour segmentation based on a physical approach and propose a new modification of segmentation algorithm. This algorithm is…
On the use of FHT, its modification for practical applications and the structure of Hough image
M. Aliev, E. I. Ershov, D. P. Nikolaev
This work focuses on the Fast Hough Transform (FHT) algorithm proposed by M.L. Brady. We propose how to modify the standard FHT to calculate sums along lines within any given range…