Color is widely remarked as one of the most demonstrative visual features, and as such it has been largely studied in the context of CBIR, thus number one to a rich variety of descriptors. As traditional color features used in CBIR, there are color histogram, color correlogram, and dominant color descriptor (DCD) [1,3,4]. A simple color similarity between two images can be measured by comparing their color histograms. The color histogram, which is a common color descriptor, indicates the occurrence frequencies of colors in the image. The color correlogram describes the probability of finding color pairs at a fixed pixel distance and provides spatial information. Therefore color correlogram yields better retrieval accuracy in comparisonto color histogram [3]. DCD is MPEG-7 color descriptors. DCD describes the salient color distributions in an image or a region of interest, and provides an effective, compact, and intuitive representation of colors presented in an image. However, DCD similarity matching does not fit human perception very well, and it will cause incorrect ranks for images with similar color distribution [5]. In Ref. [6], Yang et al. presented a color quantization method for dominant color extraction, called the linear block algorithm (LBA), and it has been shown that LBA is efficient in color quantization and computation. For the purpose of effectively retrieving more similar images from the digital image databases (DBs), Lu et al. [7] uses the color distributions, the mean value and the standard deviation, to represent the global characteristics of the image, and the image bitmap is used to represent the local characteristics of the image for increasing the accuracy of the retrieval system. Aptoula et al. [8] presen...
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...echniques are introduced. Hiremath et al. [22,23] presented novel retrieval frameworks for combining multiple image information, in which the local color and texture descriptors are captured in a coarse segmentation framework of grids.
In this paper, we propose a new content-based image retrieval technique using Zernike chromaticity distribution momentsand rotation-scale invariant Contourlet texture feature, which achieves higher retrieval efficiency. The rest of this paper is organized as follows. Section 2 presents Zernike chromaticity distribution color moments extraction. Section 3 describes the Contourlet transform and rotation-scale invariant texture representation. Section 4 contains the description of similarity measure for image retrieval. Simulation results in Section 5 will show the performance of our scheme. Finally,Section 6 concludes this presentation.
In the video named Cress Theory of Color Confrontation, the class is introduced to a professor named Dr. Frances Cress Welsing. She tells everyone during her presentation, that white supremacy exists and explains there are nine areas of people activity. There are areas that have white supremacy. But, some of those areas lack proof and evidence and they need to have it to back their claims. Those types of claims need have concrete evidence that white supremacy exists in this world, and Dr. Welsing has succeeded and failed to give it. The areas of people activity that have or lack evidence of racism are labor, law, and politics.
examines the effects of the colorblindness approach to achieving a post-racial society. Wingfield, a professor of sociology at Washington University in St. Louis and the author of numerous books and articles concerning racism in America, focuses her research around the effects of the colorblindness ideology on individual cultures and social issues. This article appears in The Atlantic, a left-leaning news source, along with a collection of Wingfield’s other articles, mostly covering issues concerning racism and segregation in America.
The Color-Blind Principle is written by Bernard Boxill discusses how color-blind and color-conscious are two very different things. This work also discusses the problems of discrimination based on something you are not responsible for such as being born black or white. Boxill uses the example of a university denying the rights of students’ admissions because their hair is parted to the right, then later states, “Suppose again for example, that a person is denied admission to law school because he parts his hair on the right side. Though he, far more easily than the black person can avoid being unfairly discriminated against, he does not thereby more easily avoid being the object, indeed, in a deeper sense, the victim, of unfair discrimination.” (463) I disagree with Boxill’s affirmative action idea because the idea of affirmative action is passing the discrimination from one race to the other.
E. D. Hirsch and Lisa Delpit are both theorist on teaching diverse students. Both of these theorist believe that when teaching diverse students, teachers need to see their students for who they are. Seeing your students for who they are, means you look past the color of your students’ skin and recognize their culture. According to Stubbs, when teachers look at their students equally, no matter the color of their skin, then the teacher is considered colorblind (2002). Being colorblind is not a great thing because we should not treat all of our students the same, since each student is different. It is important to see our students for who they are because our classes are unique. Instead, our classes represent a rainbow underclass. According to Li, the rainbow underclass is the representation of families who are culturally diverse and economically disadvantaged (2008). In order to meet these student’s needs, teachers need to think about the struggles that each student face.
The problem of the twenty century is the problem of the color-line,- the relation of the
A common characteristic of most of the images is that the neighboring pixels are highly correlated and therefore contain superfluous information. I...
Perception is defined as the awareness of the world through the use of the five senses, but the concept of perception is often used to isolate one person’s point of view, so how reliable can perception be if no one person’s is exactly the same? The word perception itself is riddled with different, well, perceptions of its meaning. When some hear the word they might automatically think of it as something innately flawed, that can easily be fooled by illusions, while others may think of its usefulness when avoiding scalding a hand on a hot stove. I am here to agree with both and to argue that perception is something necessary and helpful, and something that should be scrutinized for its flaws. By looking at perception as a way of knowing in the
Color theory encompasses a variety of definitions, concepts and design applications. Color theory to create a logical structure for the color. However, there are three main categories of color theory, which is logical and useful. They:
Contrast is the difference from dark and light or white and black in photos. In tonal contrast, the difference is between highlights, light, and dark tones. 4. What are color filters used for? What effects might different colors have?
Linear Discriminant Analysis (LDA), also known as Fisherface method, uses the Fisher’s linear discriminant criterion to overcome the limitations of eigenfaces method (Batagelj, 2006). This criterion tries to maximize the ratio of the determinant of the between-class scatter matrix of the projected samples to the determinant of the within-class scatter matrix of the projected samples. The aim is to maximize the between-class scatter while minimizing the within-class scatter.
Have you ever wondered why yellow makes you irritated? Why purple makes you feel happy? Why green calms you? Why orange helps you feel energized? Many people think that colors are just colors. But in reality, colors have been useful throughout the years as they have an huge impact on our lives. Many of us need to be aware of colors that surround us in everyday life.
In this interesting topic of the psychology of colors, the most crucial pattern is the meaning of each color and his impact on the individual as it is represented as the following:
Perception is a mysterious thing; it faces a lot of misconception, for it can merely be described as a lens, as it decides how someone views the events happening around them. Perception is the definition of how someone decides to use their senses to observe and make conceptions about events or conditions they see or that are around them. Perception also represents how people choose to observe regardless if it’s in a negative or positive way. In other words, perception can be described as people's cognitive function of how they interpret abstract situations or conjunctures around them. All in all, perception can do three things for someone: perception can change the way someone thinks in terms of their emotions and motivations, perception acts
Visual perception and visual sensation are both interactive processes, although there is a significant difference between the two processes. Sensation is defined as the stimulation of sense organs Visual sensation is a physiological process which means that it is the same for everyone. We absorb energy such as electro magnetic energy (light) or sound waves by sensory organs such as eyes. This energy is then transduced into electro chemical energy by the cones and rods (receptor cells) in the retina. There are four main stages of sensation. Sensation involves detection of stimuli incoming from the surrounding world, registering of the stimulus by the receptor cells, transduction or changing of the stimulus energy to an electric nerve impulse, and then finally the transmission of that electrical impulse into the brain. Our brain then perceives what the information is. Hence perception is defined as the selection, organisation and interpretation of that sensory input.
Digital image processing is the exercise of computer algorithms to perform image processing on digital images, as a subcategory or field of digital signal processing. Digital image processing has various advantages over analog image processing. It permits a much spacious range of algorithms to be applied to the input data and can be avoid problems such as the build-up of noise and signal distortion during processing. Since images are defined over multi dimensions digital image processing may be modeled in the form of multidimensional systems (Digital Image Processing).