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13 articles for “Color histogram”
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Content-based Image Retrieval using SURF Feature Point Descriptor and Local Binary Pattern with Color Histogram
Abstract: An important research issue in multimedia technology is the retrieval of similar objects. Most of the content-based image retrieval (CBIR) uses the low-level features such as color, shape and texture to extract the features from the images. A short time ago, the interest points are used to extract the most relevant images with different view point and transformations. Speed up Robust Feature (SURF) is robust and fast interest points detector/descriptor …
Published in Journal of Open Source Developments · Vol. 2, Issue 2, 2015 · pp. 9–15 Read article
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Effective CBIR System Using Color Histogram and Distance Measures
Abstract: AbstractInterests to precisely retrieve desired images from databases of medical images are developing every day. Certain features define the images; on the basis of those, the retrieval of images is facilitated. These components incorporate texture, color, shape and region. A lot of work has been done in this direction to discover the new ways to use these features in image retrieval process. In this study, we exhibit an overview of …
Published in Journal of Web Engineering & Technology · Vol. 6, Issue 1, 2019 · pp. 11–14 Read article
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A Survey Over Preprocessing and Similarity Matching of Trademark Images Based on Color
Abstract: Relevant retrieval from a large high dimension data set is quite cumbersome but a significant task to survive in this world of images. A company’s trademark plays an important in expansion of its business. In this paper techniques have been discussed to retrieve the trademark images on the basis of its color feature. Color is a very important part of any image. It provides strong descriptor and also helps them …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 3, 2015 · pp. 17–26 Read article
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A Survey on Content Based Image Retrieval Using Color, Texture and Shape Features
Abstract: Due to increase in volume of images in database, content based image retrieval becomes a challenging problem. To overcome such problems and efficient access of images from database, image retrieval uses low level features such as color, shape and texture that are prominent to retrieve the images. These features are extracted from the images. At last images are retrieved relevant to the query image from the database based on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 70–77 Read article
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A Survey on Content Based Image Retrieval Using Color, Texture and Shape Features
Abstract: Due to increase in volume of images in database, content based image retrieval becomes a challenging problem. To overcome such problems and efficient access of images from database, image retrieval uses low level features such as color, shape and texture that are prominent to retrieve the images. These features are extracted from the images. At last images are retrieved relevant to the query image from the database based on the …
Published in Journal of Operating Systems Development & Trends · Vol. 2, Issue 2, 2015 · pp. 1–8 Read article
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A Novel Approach to Reduce Image Retrieval Problem Using Gabor Transform, Wavelet Transform and Euclidean Distance Measure
Abstract: In the processing of image, pattern recognition and computer vision, the image retrieval is a most famous research area. Our paper presents a new method in CBIR through merging the low level feature i.e. texture, color and shape features. At first, we transform the color space from RGB model to HSV model, and then extract color histogram to form color feature vector. CBIR is the process where search of image …
Published in E-Commerce for Future & Trends · Vol. 3, Issue 1, 2016 · pp. 10–15 Read article
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An Efficient Color Method for Retrieving Color-based Images
Abstract: Image retrieval plays a vital role in many of the areas. CBIR is content-based image retrieval for browsing images from a large dataset. Image retrieval is used in many of the applications such as image processing, pattern recognition, military, medical fields and forensic fields. In the proposed image retrieval method, color method is used to extract the features and retrieve similar images based on similarity of features. In the color …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 2, 2014 · pp. 16–19 Read article
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A Brief Review on Content Based Image Retrieval with Its Techniques
Abstract: In today’s time the growth in digitization of images, diagrams, paintings and explosion of World Wide Web (www), has made classical keyword based on search for an image—an ineffective technique for the retrieval of required image documents. Content-based image retrieval (CBIR) is used to efficiently retrieve required images from fairly large databases. The main problem is to extract the image features that effectively represent image content in a database. In …
Published in Journal of Open Source Developments · Vol. 2, Issue 2, 2015 · pp. 1–8 Read article
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Review Paper for Different Techniques Using Image Enhancement
Abstract: AbstractImage enhancement (IE) performs a basic position in vision purposes. Lately, plenty of work has been carried out in the discipline of IE. Many tactics have already been proposed until now for reinforcing the digital pictures. This paper has presented a comparative analysis of quite several IE methods. This paper has proven that the fuzzy logic (FL) and histogram founded tactics have fairly amazing outcome more than the obtainable systems. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 1, 2017 · pp. 27–32 Read article
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Color Detection Using Open CV-Python
Abstract: In this study, we will identify color of different mathematical figures in the example given paired pictures, utilizing Python 2.7, Open Source PC Vision Library (Open CV) and Numpy. Open Cv could be a computer vision library developed by Intel. It is a bunch of C capacities and a couple of C++ classes that carry out broad image cycle and PC vision calculations. Some of the basic image process capabilities …
Published in Recent Trends in Programming languages · Vol. 8, Issue 1, 2021 · pp. 1–8 Read article
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Histogram Equalization for Image Enhancement Using Kidney Ultrasound Images
Abstract: Medical image processing plays an essential role in providing information in wide area for such advanced images. Kidney Ultrasound image (KUI) is an advanced medical imaging technique providing rich information about the size, shape, and location of the kidneys. KUI obtained from Doppler technique colored coded vessels is a valuable tool to help physicians to diagnose and treat various diseases. Ultrasound technology allows quick visualization of the kidneys and related …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 20–26 Read article
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Fuzzy Based Night Color Image Enhancement
Abstract: This paper presents an algorithm based on fuzzy sets for enhancement of images captured during night. HSV color space is employed to extract S and V components of the image and fuzzification is carried out on the V component. The fuzzified membership function is modified, defuzzified and three iterations are carried out. This algorithm enhances the dark region by restraining the glaring region, adjusting the contrast, distributing luminance evenly and …
Published in Current Trends in Signal Processing · Vol. 5, Issue 1, 2015 · pp. 1–6 Read article
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Various Approaches and Literature based on CBIR: A Survey
Abstract: CBIR is the assignment of retrieving the pictures from the vast accumulation of database based on their own visual substance. This paper gives the review of specially designed accomplishments in the analysis of the region of content-based image retrieval (CBIR). The requirement for the development of CBIR is enhanced as a result of giant progress in the volume of snapshots as good as the preferred software in more than one …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 2, 2018 · pp. 1–13 Read article