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The method proposed in this paper focuses on problems of motion detection and counting of very small moving objects in videos. Existing video processing methods need a defined form or a sufficient size of moving objects and do not provide accurate results in the case of very small moving objects. Many false detections can occur or many moving objects can be missed. To deal with these problems, reliability...
In this paper, we show that topological persistence can be employed in biomedical image processing to perform object segmentation. First we model the pixels of the image by combinatorial transformation into a cubical complex that we will call the pixels' complex. Then a nested sequence of complexes is built on which the persistent homology is computed. By identifying the 1D chains with large life...
This paper proposes a novel digital image water-marking method, namely SMLE, that allows to intelligently embed a gray-scale watermark image into a color host image in the wavelet domain. By decomposing a gray-scale image to binary images in digits ordering from Least Significant Bit (LSB) to Most Significant Bit (MSB), binary bits are efficiently embedded to optimal wavelet coefficient blocks using...
Most of the existing denoising algorithms are developed for grayscale images. It is not trivial to extend them for color image denoising since the noise statistics in R, G, and B channels can be very different for real noisy images. In this paper, we propose a multi-channel (MC) optimization model for real color image denoising under the weighted nuclear norm minimization (WNNM) framework. We concatenate...
In general, the three main modules of color image classification systems are: color-to-grayscale image conversion, feature extraction and classification. The color-to-grayscale image conversion is the important pre-processing step which must incorporate the significant and discriminative contrast and structure information in the converted grayscale images as in the original color image. All the existing...
In this paper, we introduce a method to generate photos from sketches using Deep Convolutional Neural Networks (DCNN). This research proposes a method by combining a network to invert sketches into photos (sketch inversion net) with a network to predict color given grayscale images (colorization net). By using this method, the quality of generated photos is expected to be more similar to the actual...
Linea nigra (LN) is a linear hyperpigmentation of skin which can appear in men developing prostate cancer. Early diagnosis of such cancer can be made by image characterization. There generally exist low contrast between LN and surrounding areas in black skin images that influences segmentation accuracy. In this paper, this problem is addressed through a multispectral analysis of RGB color images using...
Colorization is a coloring process in the image or video, which is done to provide detail and clarity to the image or video. This study used image gray scale to be colored by matching both color image pixel blocks and grayscale images based on GLCM texture feature (gray level co-occurance matrix) using a sum of absolute difference. Color image blocks are used as templates and grayscale image blocks...
The main aim of image compression is to represent the image at minimum amount of bytes. This paper presents a new algorithm that reduces number of bytes required to represent images. The proposed system divides the color image into RGB components, CMY components, YCbCr components separately and DCT and DWT are applied to each component and arithmetic coding is applied to the resultant and then their...
Online quality inspection is an effective way to guarantee the quality of PET bottles packaging on the high-speed filling production line. This paper focused on studying and developing a machine vision inspecting system for on-line defects detection of PET caps without support rings. An image processing algorithm was proposed to detecting the serious defects such as surface foreign matters and link...
We propose split-brain autoencoders, a straightforward modification of the traditional autoencoder architecture, for unsupervised representation learning. The method adds a split to the network, resulting in two disjoint sub-networks. Each sub-network is trained to perform a difficult task – predicting one subset of the data channels from another. Together, the sub-networks extract features...
This paper proposes a novel approach for colorizing near infrared (NIR) images using a Deep Convolutional Generative Adversarial Network (GAN) architecture. The proposed approach is based on the usage of a triplet model for learning each color channel independently, in a more homogeneous way. It allows a fast convergence during the training, obtaining a greater similarity between the colored NIR image...
Latent fingerprints obtained from crime scenes are rarely immediately suitable for identification purposes. Instead, most latent fingerprint images must be preprocessed to enhance the fingerprint information held within the digital image, while suppressing interference arising from noise and otherwise unwanted image features. In the following we present results of our ongoing research to assess this...
P300 speller systems represent one of the most basic applications of Brain-Computer Interfaces (BCIs). A traditional P300 speller consists of a 6 by 6 grid of characters in which each column or row in this grid intensifies at random. During such intensification process, the electroencephalography (EEG) data of the subject is recorded and analyzed to determine the character to be spelled. In this paper,...
the Active Matrix Organic Light Emitting Device (AMOLED) currently apply four sub-pixels architecture, which include a red (R), green (G), blue (B) and additional (X) sub-pixel, which has high luminous efficiency to achieve a power efficient display. Therefore, a specified algorithm would be requested to indicate which pair of sub-pixels is lighting up. In this work, we propose an available method...
In recent years, the number of cars in the world has been increasing, resulting in a rise in the importance of video-based traffic flow monitoring and counting technology. However, compared with the computerized vision-based traffic flow monitoring and counting technologies used during daytime, those used during nighttime are less developed. In view of this, we have proposed a multi-feature technology,...
Conventional skeleton extraction methods require a closed boundary constraint to solve the problem. In natural images closed boundary constraint might not be easily satisfied due to the similarity of the object and its background, occlusion, etc. In this paper a novel approach based on the Delaunay triangulation to solve the skeleton extraction in natural images is proposed. The algorithm shows a...
In image processing area and segmentation algorithms based on thresholding, the intensity of the image (grayscale) is usually obtained in order to differentiate the regions of the objects and the background. The segmentation based on the threshold works well when the image has a high intensity in the contrast, this characteristic is key to make a good classification of the pixels. This document will...
In this paper, we present an IoT-based power-efficient color frame transmission and generation algorithm for video surveillance application. The conventional way is to transmit all R, G and B components of all frames. Using our proposed technique, instead of sending all components, first one color frame is sent followed by a series of gray-scale frames. After a certain number of gray-scale frames,...
It is known that the number of colors that can be distinguished by human eye is much more than that of the grayscale levels and more information is contained in color image than what is contained in grayscale one. By studying the Structural Similarity Index (SSIM), it is found that it fails in estimating the quality of color images with color-related noises. Based on this, we develop an improved method...
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