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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...
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...
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...
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,...
Image quality assessment has been a topic of intense research over the last decades. Although its application to other disciplines is growing tremendously, its use in retinal imaging is still immature and some fundamental challenges remain unsolved. Thus, we present a research methodology for the objective assessment of the quality in retinal images. The methodology can be used as a preliminary step...
The Wireless Capsule Endoscopy is a fast growing medical technology to diagnose the internal parts of the human. It paved the way to clearly analyse the organs of the human digestive track in an efficient way. The Wireless Capsule Endoscopy is used to identify the abnormalities like Bleeding, Ulcers, Crohn's Disease etc, in the human digestive track. There are more than thousands of images from the...
This paper focuses on comparing orientation binning to perform Histograms of Oriented Gradients algorithm for the feature extraction process. The HOG algorithm comprises of gradient computation, orientation binning and block normalization aimed towards object detection. Three angles of binning are considered for (3bins, 6bins, and 9bins) with angles.64×128 image sample is taken from INRIA Person Data...
This paper deals with automatic image colorization. This is a very difficult task, since it is an ill-posed problem that usually requires user intervention to achieve high quality. A fully automatic approach is proposed that is able to produce realistic colorization of an input grayscale image. Motivated by the recent success of deep learning techniques in image processing, we propose a feed-forward,...
This paper proposes a method for transferring the RGB color spectrum to near-infrared (NIR) images using deep multi-scale convolutional neural networks. A direct and integrated transfer between NIR and RGB pixels is trained. The trained model does not require any user guidance or a reference image database in the recall phase to produce images with a natural appearance. To preserve the rich details...
With the further and faster urbanization, here come the advent and development of intelligent public transportation system. The identification of the traffic signs, as a key component of the intelligent transit system, has a prospect of widespread use in self-driving and driver assistance system. The paper focuses on the classification and identification of traffic signs based on the researches on...
Facial color is known as playing an important role in face recognition. Color face recognition has been investigated in the last decade. Recently, deep learning has attracted considerable attention due to their high performance in face recognition. The importance of the color in a deep learning framework is not fully investigated yet. In this paper, we have conducted experiments to investigate the...
Texture is considered one of most significant information sources in histo-pathology image analysis. To take advantage of information on color texture in digital histo-pathology, this work analyzes inherent characteristics of the hue component in the cylindrical color space, and introduces an effective color texture descriptor based on the LBP paradigm. Unlike existing LBP variants designed for linear...
The exponential growth of online videos imposes urgent demands on near-duplicate video detection. Near-duplicate keyframe detection is at the base of near-duplicate video detection. In this paper, based on the analysis of the state-of-the-art of near-duplicate keyframe detection, GrayScale Pyramid (GSP) is processed for improving the global feature of color histogram. By constructing the spatial pyramid...
The eye is one of the most important sensory organs in the human body. Eye disease is a common health issues around the world. Two such diseases are cataract and conjunctivitis. Cataract causes a sort of clouding on the lens leading to reduced vision and if kept untreated for long leads to permanent blindness. Conjunctivitis or pink eye is a condition where the conjunctiva of the eye is inflamed by...
The popularity of smartphones usage especially Android mobile platform has increased to 80% of share in global smartphone operating systems market, as a result of which it is on the top in the attacker's target list. The fact of having more private data and low security assurance letting the attacker to write several malware programs in different ways for smartphone, and the possibility of obfuscating...
The rapid growth of different types of images has posed a great challenge for scientific fraternity across the world. For easy access to large number of images, efficient indexing and retrieval is required. The field of Content-Based Image Retrieval (CBIR) attempts to solve this problem. This paper proposes a combination of local and global features for CBIR. Local features are extracted through Scale...
This paper describes different approaches for detection and identification of diseases in apples using computer vision. Our proposed algorithms analyze surface appearance of apple for defects using image features, viz. color and texture. For segmentation of Region Of Interest (ROI), K-means clustering is performed over the image pixels based on their intensity values. For creation of feature vector,...
System of traditional Chinese medicine has always been emphasized by people, have heavy depending on the individual difference factors in disease, the role of development, this kind of subtle change, tongue can fast and accurate present right now. Using tongue diagnosis to identification of traditional Chinese medicine (TCM) physique, which in clinical can be applied to the health, health physical...
The presence of inflammatory cells complicates the process of identifying the nuclei in the early detection of cervical cancer. Inflammatory cells need to be eliminated to assist pathologists in reading Pap smear slides. The texture of Grey-Level Run-Length Matrix (GLRLM) for inflammatory cells and nuclei types are investigated. The inflammatory cells and nuclei have different texture, and it can...
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