Geometric-based nail segmentation for clinical measurements
A robust segmentation method that can be used to perform measurements on toenails is presented. The proposed method is used as the first step in a clinical trial to objectively quantify the incidence of a particular pathology. For such an ...
Multiple organ-specific cancers classification from PET/CT images using deep learning
As the number of cancer cases increases and the popularity of positron emission tomography/computed tomography (PET/CT), an automated cancer screening system that can assist radiologists is desired. The existing methods based on PET/CT images are ...
Traffic signs detection and recognition systems by light-weight multi-stage network
Traffic sign detection and recognition (TSDR) plays an important role in the fields for assistant driving, autonomous vehicle and so on. However, due to the complexity of real driving scene and variety of traffic signs, many challenging problems ...
Detection of hydrocephalus using deep convolutional neural network in medical science
Hydrocephalus is a generally known disease found in the central nervous system and requires neurosurgical treatment. However, there is no prevalent solution and effective method for precise detection. This paper introduces Hydrocephalus detection ...
Procedural modeling of plant ecosystems maximizing vegetation cover
Vegetation plays a major role in the realistic display of outdoor scenes. However, manual plant placement can be tedious. For this reason this paper presents a new proposal in the field of procedural modeling of natural scenes. This method creates ...
The recommendation of satisfactory product for new users in social commerce website
Recommending the post-use satisfactory product for new users can allow more effectively escalating the sale of products and expanding the new customers. When recommending a post-use satisfactory product for new users, the existing methods often ...
Fusing color, depth and histogram maps for saliency detection
A noval scheme is presented to identify image’s saliency. The proposed scheme formalizes the saliency map using color, depth along with input histogram. The color saliency map assumes that the salient objects in an image are usually more colorful ...
Fruit quality evaluation using machine learning techniques: review, motivation and future perspectives
In the field of agriculture and food processing, quality evaluation is a significant parameter to increase benefits and accommodations for individual life. The presence of diseases and pesticides is additionally the major factor that emerges the ...
A pseudo-random pixel mapping with weighted mesh graph approach for reversible data hiding in encrypted image
In recent years, reversible data hiding (RDH) in encrypted images got much attention due to its wide applications in the areas such as cloud computing, military image transmission, medical image transmission, etc. This paper introduces a new ...
Peach surface defect identification of complex background based on IDCNN and GWOABC-KM
This paper presents a peach surface defect recognition method based on GWOABC-KM (Gray Wolf algorithm and K-means optimized by improved bee swarm algorithm). Firstly, aiming at the problem of poor sharpness and noise in peach images taken in ...
RETRACTED ARTICLE: Intelligent model to image enrichment for strong night-vision surveillance cameras in future generation
Images, which are captured in the night, have the poor quality in comparison to day light. In surveillance cameras, because of weather and other constraint images have low brightness, low contrast, and high noise. We need night vision in various ...
Image encryption scheme for multi-focus images for visual sensors network
Image fusion is the technique to obtain an image, possessing spatially and spectrally enhanced as compared to the individual high spatial and high spectral images. After obtaining a detailed image, propagation over an insecure channel is a ...
Fast coding unit size decision based on deep reinforcement learning for versatile video coding
Video coding has long been looking for a more available approach than the greedy method. The quad-tree with nested multi-type tree (QTMT) structure including quad-tree (QT) and multi-type tree (MTT) results in highly coding complexity in Versatile ...
Skin lesion image classification method based on extension theory and deep learning
A skin lesion is a part of the skin that has abnormal growth on body parts. Early detection of the lesion is necessary, especially malignant melanoma, which is the deadliest form of skin cancer. It can be more readily treated successfully if ...
Truncating fined-tuned vision-based models to lightweight deployable diagnostic tools for SARS-CoV-2 infected chest X-rays and CT-scans
In such a brief period, the recent coronavirus (COVID-19) already infected large populations worldwide. Diagnosing an infected individual requires a Real-Time Polymerase Chain Reaction (RT-PCR) test, which can become expensive and limited in most ...
A novel framework for brain tumor detection based on convolutional variational generative models
Brain tumor detection can make the difference between life and death. Recently, deep learning-based brain tumor detection techniques have gained attention due to their higher performance. However, obtaining the expected performance of such deep ...
Performance analysis on dictionary learning and sparse representation algorithms
Theoretically, the Super-Resolution (SR) reconstruction scheme is a method which is performed by many applications nowadays for the purpose of generating a High-Resolution (HR) image using the input Low-Resolution (LR) images by filling in the ...
Face recognition in a large dataset using a hierarchical classifier
Face recognition is one of the most common authentication methods. Although much research has been conducted in this area, there are still many challenging issues to be addressed on face recognition, such as a large number of images in a dataset, ...
Pedestrian traffic lights and crosswalk identification
People who experience physical or visual impairments depend on family members or caregivers to accomplish their activities. For the physically impaired, the adoption of electric-powered wheelchairs remedies the effects of lost mobility, providing ...
A content-based intra rate-distortion model for HEVC-SCC
Screen content (SC) videos have different characteristics compared to camera-captured videos. New encoding modes such as Intra Block Copy (IBC) and Palette modes have been introduced to the SC coding (SCC) extension of the high-efficiency video ...
Detection of tartrazine colored rice flour adulteration in turmeric from multi-spectral images on smartphone using convolutional neural network deployed on PaaS cloud
Food adulteration occurs globally, in many facets, and affects almost all food commodities. Adulteration is not just a crucial economic problem, but it may also lead to serious health problems for consumers. Turmeric (Curcuma longa) is a world-...
Internet of vehicles: concept, process, security aspects and solutions
Internet of Vehicles (IoV) is a new concept, derived from combining VANET and Internet of Things (IoT), aiming at increasing road’ user safety and reducing the number of accidents. In IoV, different types of communication are possible, namely, ...
Research on multi-image and multi-parameter fusion algorithm based on detail restoration
In order to improve the contrast, clarity and color fidelity of low illumination image, reduce the negative impact of image degradation, in this paper, we propose an image clarity scheme based on multi-image multi-parameter and multi-scale fusion. ...
An efficient object detection system for indoor assistance navigation using deep learning techniques
Building new systems used for indoor objects detection and indoor assistance navigation presents a very crucial task especially in artificial intelligence and computer science fields. The number of blind and visually impaired persons (VIP) is ...
Two-stage content based image retrieval using sparse representation and feature fusion
With the advent of large-scale databases in the last two decades, content based image retrieval (CBIR) has been widely investigated. Studies show that the performance of the CBIR system is mainly affected by the image descriptors and the ...
Digital image noise removal based on collaborative filtering approach and singular value decomposition
Image denoising is a crucial step in order to improve digital image quality. Furthermore, the digital image in sparse format especially in low-rank structure has been utilized in several multimedia applications. Non-local similarity algorithm is ...
The identities of n-dimensional s-transform and applications
The Stockwell transform is a signal processing tool based on Fourier transform (FT) with a specific window function. The important properties of 1-dimensional (1-D) and 2-dimensional (2-D) S-transform (ST) are available in the literature. This ...
Cryptanalysis and enhancement of image encryption scheme based on word-oriented feed back shift register
In the recent past, an image encryption scheme has been proposed by Deb et al., based on the Logistic map, Arnold transformation, and word-oriented feedback shift register (wfsr). In this scheme, first the plain image is randomized and scrambled ...
Boosting Marine Predators Algorithm by Salp Swarm Algorithm for Multilevel Thresholding Image Segmentation
Pixel rating is considered one of the commonly used critical factors in digital image processing that depends on intensity. It is used to determine the optimal image segmentation threshold. In recent years, the optimum threshold has been selected ...