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"We propose the use of convolutional neural networks (CNN) for counting and positioning people in visible and infrared images. Our data set is made of semi-artificial images created from real photographs taken from a dro...

Complementary DNA (cDNA) microarrays are a powerful high throughput technology developed in the last decade allowing researchers to analyze the behaviour and interaction of thousands of genes simultaneously. The large am...

Segmentation is often a critical step in image analysis. Microscope image components show great variability of shapes, sizes, intensities and textures. An inaccurate segmentation conditions the ulterior quantification a...

In some cases, low resolution of those images composing a video film hinders the proper visual interpretation of its data. A typical example of this is video obtained from security cameras. There thus exists the need to ...

Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniqu...

"Confocal microscope images are wide useful in medical diagnosis and research. The automatic interpretation of this type of images is very important but it is a challenging endeavor in image processing area, since these ...

"SAR (synthetic aperture radar) and PolSAR (polarimetric synthetic aperture radar) images fulfill a fundamental role in Earth observation, due to their advantages over optical images. However, the presence of speckle noi...

Images compression is a widely studied topic. Conventional situations offer variable compression ratios depending on the image in question and, in general, do not yield good results for images that are rich in tones. Thi...

Tissue classification in Magnetic Resonance (MR) brain images is an important issue in the analysis of several brain dementias. This paper presents a modification of the classical K-means algorithm taking into account th...

UAV (Unmanned Airborne Vehicle) high resolution digital image acquisition systems based on small format cameras provide a versatile alternative to the solution of environmental monitoring and remote sensing problems. Thr...

The identification and classification of seeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in ocular inspection one should consider seed size, shape, ...

Segmentation in biological images is essential for the determination of biological parameters that allow the construction of models of several biological problems. This helps to establish clear relationships between thos...

In this paper, an efficient algorithm for detecting frontalview faces in color images is proposed. The proposed algorithm has a special task; it detects faces in the presence of skin-tone regions such as human body, clot...

In a general context we introduce image processing with 1-dimensional wavelets and show the diferences with nonseparable 2-dimensional wavelets having quincunx decimation, in the first place, and with balanced nonseparab...

In this paper, an improvement of deformable template matching algorithm for polygonal objects in grayscale images using two-dimensional deformable templates along orthogonal curves is presented. In the process of pre-com...

"Synthetic Aperture Radar (SAR) imaging is based on airborne or satellite active microwave sensors that can capture the earth surface by emitting a signal and receiving the backscattered signal that forms the resulting ...

The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such ...

Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture de...

We present the automated techniques we have developed for new software that optimally detects, deblends, measures and classifies sources from astronomical images: SExtractor (Source Extractor ). We show that a very relia...

Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrar...