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Dithering or error diffusion is a technique used to obtain a binary image, suitable for printing, from a grayscale one. At each step, the algorithm computes an allowed value of a pixel from a grayscale one, applying a threshold and, therefore, causing a conversion error. To obtain the optical illusion of a continuous tone, the…

Facial emotion recognition is one among many popular and challenging tasks in the field of computer vision. Numerous researches have been conducted on this task and each proposed either standalone- or ensemble-based processing technique. While many researches strive for better accuracy, this research also attempts to increase the processing efficiency of computer correctly classifying human…

In this paper, performances of two variations of chaos based algorithms are compared. First algorithm is a self-adaptive color image encryption algorithm is proposed based on Radial Hilbert Transform and chaos. This technique uses chaotic random phase masks operated on the transformed pixels to increase the randomness in confusion and diffusion operations. Also, a random…

A real-time embedded system requires plenty of measurements to fallow the Nyquist criteria. The hardware built for such a large number of measurements, is facing the challenges like storage and transmission rate. Practically it is very much complex to build such costly hardware. Compressive Sensing (CS) will be a future alternate technique for the Nyquist…

This paper presents a comparative study for using the classic networks in remote sensing images classification. There are four deep convolution models that used in this comparative study; the DenseNet 196, the NASNet Mobile, the VGG 16, and the ResNet 50 models. These learning convolution models are based on the use of the ImageNet pre-trained…

Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…

Age and growth are two essential rice biophysics parameters used to determine the health parameters and production rate. The spatial data of both parameters can utilize remote sensing technology, which in turn makes use of several vegetation indices to achieve accurate estimation. However, due to the rapid changes in rice plants’ characteristics, it is essential…

Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID-19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing number…

With the aim of preventing hydro-geological risks and overcoming the problems of current rain gauges, this paper proposes a low-complexity and cost-effective video rain gauge. In particular, in this paper the authors propose a new approach to rainfall classification based on image processing and video matching process employing convolutional neural networks (CNN). The system consists…

Image description generation is an important area in Computer Vision and Natural Language Processing. This paper introduces a novel architecture for an image description generation system using keywords. The proposed architecture uses a high-level feature such as keywords for generating captions. The important component of caption generation is the deep Bidirectional LSTM network. The space…

In Peru, approximately since 2013, a necessary change has begun in the importance given to research, science, technology, and technological innovation. Likewise, in 2014, a new University Law was approved that among other aspects also promotes research production in universities. Against this context, the universities begin to improve with more emphasis activities related to research.…

Recently, digital image forgery detection is an emergent and important area of image processing. Digital image plays a vital role in providing evidence for any unusual incident. However, the image forgery my hide evidence and prevents the detection of such criminal cases due to advancement in image processing and availability of sophisticated software tamper of…

Most buildings are equipped with various types of sensors to detect smoke in the event of a fire, though most are located internally. Practically, smoke has to reach the sensor in order for the sensor to react. The limitations of these sensors are their inability to respond in the early stages of a fire, and…

Dry Eye Disease (DED) is one of the commonly occurring chronic disease today, affecting the vision of eye. It causes severe discomfort in eye, visual disturbance and blurred vision impacting the quality of life of patients. Due to recent advancements in Artificial Intelligence (AI) and rapid progress of analytics techniques, several image modality based computerized…

Face recognition in low resolution images has challenges in active research because face recognition is usually implemented in high resolution images (HR). In general, research leads to a combination of pre-processing and training models. Therefore, this study aims to classify low-resolution face images using a combination of pre-processing and deep learning. In addition, this study…

This paper discusses a new Tone Mapping (TM) approach converting a High Dynamic Range (HDR) image into a Low Dynamic Range (LDR) image able at the same time to extract the relevant details and enhance the contrast of LDR images to ensure a good LDR image visual quality. This approach uses an advantage of multiresolution…

Object Instance Recognition aims to classify objects specifically and usually use a single reference image. It is possible to be used in many applications such as visual search, information retrieval and augmented reality. However, various things affect the appearance of the objects, which makes the recognition process harder, especially if a single reference image is…

Blurred small objects produced by cropping, warping, or intrinsically so, are challenging to detect and classify. Therefore, much recent research is focused on feature extraction built on Faster R-CNN and follow-up systems. In particular, RPN, SPP, FPN, SSD, and DSSD are the layered feature extraction methods for multiple object detections and small objects. However, super-resolution…

In the present article, we introduce a foveation-based optimized embedded and its optimized version image coders thereafter called VOEFIC/MOEFIC and its related foveation wavelet visible difference predictor FWVDP coding quality metric. It advances a visually advanced foveal weighting mask that regulates the wavelet-based image spectrum before its encoding by the SPIHT encoder. It intends to…

Medical images are transmitted via the Internet or the hospital intranet which include many important information about the patient’s personal information. Medical image encryption is a technology that can effectively protect the information contained in these medical images. In this paper, we give a secure and trusty Combined Cellular Automata (CoCA) based medical image encryption…

The Braille language system or also known as the language for the blind people was created so that these people can understand the vocabulary words depending on the country in which they are located, this system is based on points in which the points raised or also known as the largest points depending on their…

This paper proposes an algorithm aimed at quantifying the expression of KI-67 protein in digital images of breast biopsy tissue samples obtained through an optical microscope. The algorithm allows to obtain a report on the quantity of non-proliferating and proliferating cells through the detection and quantification of KI-67. The sample analysis via software aims to…

In times of crisis or traumatic transformation processes, one of the most frequent negative externalities is that the self-image of a city deteriorates among its stakeholders, which affects their economic and social expectations and decisions. The internalisation of this externality must be a key objective for the local public manager so that any initiative can…

Synthetic aperture radar (SAR) is an imaging device mounted on a moving platform. Its ability to identify a weak target from a nearby strong one depends upon the peak side lobe ratio (PSLR). This paper is intended to ameliorate such important ratio through the use of windowing of the transmitted pulse and studying the noise…

Over the past decades, huge efforts have been devoted for image enhancement under uncontrolled scene such as fog and haze. This work proposes Multi-stage de-hazing approach for improving the quality of hazy images. Four main stages are introduced, in our approach, to achieve an automated, efficient and robust de-hazy processing. The first two stages are…