Search Results

Analyzing large sets of visual media remains a challenging task, particularly in mixed-method studies dealing with problematic information and human subjects. Using AI tools in such analyses risks reifying and exacerbating biases, as well as untenable ...

This study explores an innovative method for generating color themes from images using Convolutional Neural Networks (CNNs). Grounded in the integration of the Munsell color system for accurate color categorization and Mini Batch K-means for effective ...

• We present a novel hybrid model composed of a convolutional autoencoder and a Growing Hierarchical Bregman Neural Gas (GHBNG) for hierarchical color ...

Color quantization (CQ) is one of the most common and important procedures to be performed on digital images. In this paper, a new approach to hierarchical color quantization is described, presenting a novel neural network architecture ...

Most of the applications of modern day VLSI designs are approaching towards energy efficient and high speed computing solutions. Approximate computing is considered a suitable design methodology that satisfies the current requirements of hardware and ...

A video scene can be defined as a fixed subdivision of a video, or a group of video frames having the same semantic contents. This paper presents a method to perform scene classification under unsupervised clustering environment. A holistic ...

Color quantization is a common image processing technique where full color images are to be displayed using a limited palette of colors. The choice of a good palette is crucial as it directly determines the quality of the resulting image. Standard ...

In this paper, we propose a non-parametric approach for shot boundary detection in videos. The proposed method exploits the split and merge framework by the use of color histograms. Initially, every frame of the input video sequence undergoes color ...

Online Social Networks (OSNs) provide reliable communication among users from different countries. The volume of texts generated by OSNs is huge and highly informative. Gender classification can serve commercial organizations for advertising, law ...

For the monitoring of crop in greenhouse with machine vision, it is difficult to extract the leaf images from natural light background, having poor imaging conditions and different plant material. To settle the problem, a color image segmentation ...

We present an automatic method that can be used to abstract high resolution images into very low resolution outputs with reduced color palettes in the style of pixel art. Our method simultaneously solves for a mapping of features and a reduced palette ...

Color quantization (CQ) is one of the most important techniques in image compression and processing. Most of quantization methods are based on clustering algorithms. Data clustering is an unsupervised classification technique and belongs to NP-hard ...

In order to improve the efficiency of the analysis of building color, and enhance the objectivity of evaluation, we propose a novel method to analyze and evaluate the color of urban architecture. First, a developed K-means clustering algorithm is ...

A typical CS2 course introduces the concepts of ADTs and data structures along with an introduction to algorithm analysis. A main objective of the course is the expectation that students will gain an appreciation of the impact the choice of data ...

Color and shape descriptions of an image are the most widely used visual features in content-based image retrieval systems. Feature vectors for shape and color can be combined to improve the performance of the content-based image retrieval systems. In ...

We first research the low-layer physical feature of image, retrieval the image by color features, and import the technique of relevance feedback. By cooperation between human and computer, Making up the computer’s limited ability of understanding and ...

This paper presents the development of a three level unsupervised segmentation framework based on color and texture features. An important contribution of this work consists of a new formulation of three different clustering algorithms at three ...

Color quantization is an important operation with many applications in graphics and image processing. Most quantization methods are essentially based on data clustering algorithms. However, despite its popularity as a general purpose clustering ...

A new method is proposed for initializing Kohonen's selforganizing feature maps (SOFM) of fixed zero neighborhood radius for use in color quantization. The method employs the two largest principal components of the input image so that the initial ...

A color quantization method is presented, which is based on the analysis of the histogram at different resolutions computed on a Gaussian pyramid of the input image. Criteria based on persistence and dominance of peaks and pits of the histograms are ...

This paper presents a novel similarity measure method based a combination of color and texture feature representations. In this method, the YIQ color space is chosen, because it can describe both color images and gray images and the transform from RGB ...