When Too Similar Is Bad: A Practical Example of the Solar Dynamics Observatory Content-Based Image-Retrieval System

Banda, Juan M.; Schuh, Michael A.; Wylie, Tim; McInerney, Patrick; Angryk, Rafal A.

doi:10.1007/978-3-319-01863-8_10

Cited by 8 publications

(3 citation statements)

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“…Returning the most similar image is an intrinsic characteristic of a properly functioning CBIR system, but our domain-specific problem of too many similar images makes this characteristic a less desired effect. In preliminary analyses, we proposed some insights into mitigating this general issue within the system (Banda et al, 2014b), and a fully-fledged production system can also include simple date/time search filters to supplement the underlying CBIR system mechanisms.…”

Section: Similarity Plotsmentioning

confidence: 99%

On visualization techniques for solar data mining

Schuh

Banda

Wylie

et al. 2015

Astronomy and Computing

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Section: Similarity Plotsmentioning

confidence: 99%

On visualization techniques for solar data mining

Schuh

Banda

Wylie

et al. 2015

Astronomy and Computing

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“…A background surface BS is then computed by following two rules: For zero pixels in image B the corresponding value at BS image equals to imf corresponding values. For the foreground pixels the corresponding values of the BS image are computed via interpolation described in the following equations: (14) otherwise (15) The window size of dx x dy is set to 5x5.…”

Section: Edge Detection Pointsmentioning

confidence: 99%

“…A wide variety of CBIR have already been proposed in the literature (e.g. [11][12][13][14][15][16]).…”

Section: Introductionmentioning

confidence: 99%

Content Based Image Retrieval and Its Application to Product Recognition

Alvanitopoulos

Moroi

Bagropoulos

et al. 2015

IFIP Advances in Information and Communication Technology

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Part 1: Image Processing and AnalysisInternational audienceProduct Recognition is a challenging problem in many practical applications. This paper presents a new approach for product recognition. By utilizing a set of crawlers our task is to extract informative content from web pages and automatically recognize products found on web pages. A set of images is extracted from each web page and then a new “content-based” image retrieval technique is performed to rank the images from our product catalog. The proposed content-based image retrieval technique utilizes the Empirical Mode Decomposition and processes the first extracted component of the source image. This component maintains the highest local spatial variations of the source image. An adaptive local-threshold technique is applied for the extraction of edges. A quantized and normalized histogram is created for the representation of images. Simulation results reveal that the proposed method is a promising tool for the challenge task of product recognition

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