H.5. Image Processing and Computer Vision
Automatic Brain Tumor Detection in Brain MRI Images using Deep Learning Methods

Farima Fakouri; Mohsen Nikpour; Abbas Soleymani Amiri

Articles in Press, Accepted Manuscript, Available Online from 24 February 2024


  Due to the increased mortality caused by brain tumors, accurate and fast diagnosis of brain tumors is necessary to implement the treatment of this disease. In this research, brain tumor classification performed using a network based on ResNet architecture in MRI images. MRI images that available in the ...  Read More

H.5. Image Processing and Computer Vision
Using Convolutional Neural Network to Enhance Classification Accuracy of Cancerous Lung Masses from CT Scan Images

Mohammad Mahdi Nakhaie; Sasan Karamizadeh; Mohammad Ebrahim Shiri; Kambiz Badie

Volume 11, Issue 4 , November 2023, , Pages 547-559


  Lung cancer is a highly serious illness, and detecting cancer cells early significantly enhances patients' chances of recovery. Doctors regularly examine a large number of CT scan images, which can lead to fatigue and errors. Therefore, there is a need to create a tool that can automatically detect and ...  Read More

H.5. Image Processing and Computer Vision
An Optimal Hybrid Method to Detect Copy-move Forgery

Fatemeh Zare mehrjardi; Alimohammad Latif; Mohsen Sardari Zarchi

Volume 11, Issue 3 , July 2023, , Pages 429-442


  Image is a powerful communication tool that is widely used in various applications, such as forensic medicine and court, where the validity of the image is crucial. However, with the development and availability of image editing tools, image manipulation can be easily performed for a specific purpose. ...  Read More

H.5. Image Processing and Computer Vision
A New Scheme for Lossless Meaningful Visual Secret Sharing by using XOR Properties

Z. Mehrnahad; A.M. Latif; J. Zarepour Ahmadabadi

Volume 11, Issue 2 , April 2023, , Pages 195-211


  In this paper, a novel scheme for lossless meaningful visual secret sharing using XOR properties is presented. In the first step, genetic algorithm with an appropriate proposed objective function created noisy share images. These images do not contain any information about the input secret image and ...  Read More

H.5. Image Processing and Computer Vision
A Novel Content-based Image Retrieval System using Fusing Color and Texture Features

S. Asadi Amiri; Z. Mohammadpoory; M. Nasrolahzadeh

Volume 10, Issue 4 , November 2022, , Pages 559-568


  Content based image retrieval (CBIR) systems compare a query image with images in a dataset to find similar images to a query image. In this paper a novel and efficient CBIR system is proposed using color and texture features. The color features are represented by color moments and color histograms of ...  Read More

H.5. Image Processing and Computer Vision
Sparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains

S. Mavaddati

Volume 8, Issue 2 , April 2020, , Pages 161-175


  In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification ...  Read More

H.5. Image Processing and Computer Vision
Statistical Wavelet-based Image Denoising using Scale Mixture of Normal Distributions with Adaptive Parameter Estimation

M. Saeedzarandi; H. Nezamabadi-pour; S. Saryazdi

Volume 8, Issue 2 , April 2020, , Pages 289-301


  Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the ...  Read More

H.5. Image Processing and Computer Vision
Segmentation Assisted Object Distinction for Direct Volume Rendering

A. Azimzadeh Irani; R. Pourgholi

Volume 8, Issue 1 , January 2020, , Pages 67-82


  Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently ...  Read More

H.5. Image Processing and Computer Vision
Morphological Exudate Detection in Retinal Images using PCA-based Optic Disc Removal

J. Darvish; M. Ezoji

Volume 7, Issue 4 , November 2019, , Pages 487-493


  Diabetic retinopathy lesion detection such as exudate in fundus image of retina can lead to early diagnosis of the disease. Retinal image includes dark areas such as main blood vessels and retinal tissue and also bright areas such as optic disk, optical fibers and lesions e.g. exudate. In this paper, ...  Read More

H.5. Image Processing and Computer Vision
Video Abstraction in H.264/AVC Compressed Domain

A. R. Yamghani; F. Zargari

Volume 7, Issue 4 , November 2019, , Pages 521-535


  Video abstraction allows searching, browsing and evaluating videos only by accessing the useful contents. Most of the studies are using pixel domain, which requires the decoding process and needs more time and process consuming than compressed domain video abstraction. In this paper, we present a new ...  Read More

H.5. Image Processing and Computer Vision
A Novel Face Detection Method Based on Over-complete Incoherent Dictionary Learning

S. Mavaddati

Volume 7, Issue 2 , April 2019, , Pages 263-278


  In this paper, face detection problem is considered using the concepts of compressive sensing technique. This technique includes dictionary learning procedure and sparse coding method to represent the structural content of input images. In the proposed method, dictionaries are learned in such a way that ...  Read More

H.5. Image Processing and Computer Vision
Compressed Image Hashing using Minimum Magnitude CSLBP

V. Patil; T. Sarode

Volume 7, Issue 2 , April 2019, , Pages 287-297


  Image hashing allows compression, enhancement or other signal processing operations on digital images which are usually acceptable manipulations. Whereas, cryptographic hash functions are very sensitive to even single bit changes in image. Image hashing is a sum of important quality features in quantized ...  Read More

H.5. Image Processing and Computer Vision
Pedestrian Detection in Infrared Outdoor Images Based on Atmospheric Situation Estimation

Seyed M. Ghazali; Y. Baleghi

Volume 7, Issue 1 , January 2019, , Pages 1-16


  Observation in absolute darkness and daytime under every atmospheric situation is one of the advantages of thermal imaging systems. In spite of increasing trend of using these systems, there are still lots of difficulties in analysing thermal images due to the variable features of pedestrians and atmospheric ...  Read More

H.5. Image Processing and Computer Vision
Parallel Spatial Pyramid Match Kernel Algorithm for Object Recognition using a Cluster of Computers

A. Asilian Bidgoli; H. Ebrahimpour-Komle; M. Askari; Seyed J. Mousavirad

Volume 7, Issue 1 , January 2019, , Pages 97-108


  This paper parallelizes the spatial pyramid match kernel (SPK) implementation. SPK is one of the most usable kernel methods, along with support vector machine classifier, with high accuracy in object recognition. MATLAB parallel computing toolbox has been used to parallelize SPK. In this implementation, ...  Read More

H.5. Image Processing and Computer Vision
Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

M. Amin-Naji; A. Aghagolzadeh

Volume 6, Issue 2 , July 2018, , Pages 233-250


  The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced ...  Read More

H.5. Image Processing and Computer Vision
Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images

M. Shakeri; M.H. Dezfoulian; H. Khotanlou

Volume 6, Issue 1 , March 2018, , Pages 1-12


  Histogram Equalization technique is one of the basic methods in image contrast enhancement. Using this method, in the case of images with uniform gray levels (with narrow histogram), causes loss of image detail and the natural look of the image. To overcome this problem and to have a better image contrast ...  Read More

H.5. Image Processing and Computer Vision
Automatic Optic Disc Center and Boundary Detection in Color Fundus Images

F. Abdali-Mohammadi; A. Poorshamam

Volume 6, Issue 1 , March 2018, , Pages 35-46


  Accurately detection of retinal landmarks, like optic disc, is an important step in the computer aided diagnosis frameworks. This paper presents an efficient method for automatic detection of the optic disc’s center and estimating its boundary. The center and initial diameter of optic disc are ...  Read More

H.5. Image Processing and Computer Vision
Iris localization by means of adaptive thresholding and Circular Hough Transform

S. Memar Zadeh; A. Harimi

Volume 5, Issue 1 , March 2017, , Pages 21-28


  In this paper, a new iris localization method for mobile devices is presented. Our system uses both intensity and saturation threshold on the captured eye images to determine iris boundary and sclera area, respectively. Estimated iris boundary pixels which have been placed outside the sclera will be ...  Read More

H.5. Image Processing and Computer Vision
A stack-based chaotic algorithm for encryption of colored images

H. Khodadadi; O. Mirzaei

Volume 5, Issue 1 , March 2017, , Pages 29-37


  In this paper, a new method is presented for encryption of colored images. This method is based on using stack data structure and chaos which make the image encryption algorithm more efficient and robust. In the proposed algorithm, a series of data whose range is between 0 and 3 is generated using chaotic ...  Read More

H.5. Image Processing and Computer Vision
Image authentication using LBP-based perceptual image hashing

R. Davarzani; S. Mozaffari; Kh. Yaghmaie

Volume 3, Issue 1 , March 2015, , Pages 21-30


  Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary ...  Read More

H.5. Image Processing and Computer Vision
Modified CLPSO-based fuzzy classification System: Color Image Segmentation

A.M. Shafiee; A. M. Latif

Volume 2, Issue 2 , July 2014, , Pages 167-179


  Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting ...  Read More