Spatial layout representation for query-by-sketch content-based image retrieval

Sciascio, Eugenio Di; Donini, Francesco M.; Mongiello, Marina

doi:10.1016/s0167-8655(02)00124-1

Cited by 19 publications

(8 citation statements)

References 14 publications

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“…The aim is to show the degree of rotation and scale invariance for these approaches. There are some other approaches for SBIR such as [10], introduced by Di Sciascio et al, but since they need image segmentation at the preprocessing stage and the queries contain color and texture attributes, they are not applicable to this study.…”

Section: Comparative Resultsmentioning

confidence: 99%

“…The MPEG-7 standard defines descriptors derived from three main image content features: color, texture, and shape [8], [9]. VisualSEEk and the algorithm proposed by Di Sciascio et al [10] consider the spatial object layout as a significant content feature complementing color and texture attributes.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], several dominant points are extracted for each contour using information derived from the convex hull and the contour curvature. Query-by-sketch is adequately investigated in [10] using the spatial relationships between shapes in an image. The approach introduces a way to represent shapes, their spatial arrangement, and color and texture attributes in the user sketch.…”

Section: Introductionmentioning

confidence: 99%

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Sketch-Based Image Matching Using Angular Partitioning

Chalechale

Naghdy

Mertins

2005

IEEE Trans. Syst., Man, Cybern. A

136

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Abstract-This paper presents a novel method for image similarity measure, where a hand-drawn rough black and white sketch is compared with an existing data base of full color images (art works and photographs). The proposed system creates ambient intelligence in terms of the evaluation of nonprecise, easy to input sketched information. The system can then provide the user with options of either retrieving similar images in the database or ranking the quality of the sketch against a given standard, i.e., the original image model. Alternatively, the inherent pattern-matching capability of the system can be utilized to allow detection of distortion in any given real time-image sequences in vision-driven ambient intelligence applications. The proposed method can cope with images containing several complex objects in an inhomogeneous background. Two abstract images are obtained using strong edges of the model image and the morphologically thinned outline of the sketched image. The angular-spatial distribution of pixels in the abstract images is then employed to extract new compact and effective features using the Fourier transform. The extracted features are rotation and scale invariant and robust against translation. Experimental results from seven different approaches confirm the efficacy of the proposed method in both the retrieval performance and the time required for feature extraction and search.

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Section: Comparative Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sketch-Based Image Matching Using Angular Partitioning

Chalechale

Naghdy

Mertins

2005

IEEE Trans. Syst., Man, Cybern. A

136

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show abstract

“…The visual features including color, shape and texture are unable to precisely capture the high-level semantics of images. On the contrary, spatial relationships among image objects often capture the most relevant and regular part of information of an image [16][17][18][19]. However, it is difficult to separate meaningful objects from an image automatically due to the lack of a complete image understanding model.…”

Section: Similarity Measurement By Dynamic Programmingmentioning

confidence: 99%

Speeding up the similarity search in high-dimensional image database by multiscale filtering and dynamic programming

Cheng

2006

Image and Vision Computing

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“…Typically, PHOTOBOOK would retrieve the images indexed by similar features with user's query, which is described by an example image [7][17] [18]. In order to also retrieve the relevant images taking layouts of colors and shapes similar with the query, QBIC can exploit an image sketched by users as a query [9][15] [20]. Therefore, it is the advantage that this model can automatically index a massive volume of images by their features [8] [19].…”

Section: Introductionmentioning

confidence: 99%

<title>Design and implementation of a concept-based image retrieval system with edge description templates</title>

Choi

Park

2003

Storage and Retrieval Methods and Applications for Multimedia 2004

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In this paper, we design and implement a concept-based image retrieval system using feature information, more specifically, edge histogram description. The general edge histogram framework is a novel index mechanism which allows us to describe a content of images. However, there is a significant drawback in the framework that it can not accommodate a concept-based retrieval. Even if images are only conceptually related with user queries, it may be capable of proving them to be irrelevant since their features can be different each other. Our system adapts an edge histogram descriptor and includes a knowledge used for capturing concepts from images. In the knowledge base, a concept is expressed as some of templates, which can be described by common edge histograms for the images to represent the concept well. The templates can be generated by clustering the training images related with a concept. Consequently, since an image can also be matched with some of the templates, our system is able to support an automatic mechanism for indexing the image with the concept. The indexing mechanism enables users to retrieve the images related with a query which is formulated with their intended concepts. In addition, we also demonstrate that our concept-based approach makes a favorable comparison with an approach based on color or edge features.

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Spatial layout representation for query-by-sketch content-based image retrieval

Cited by 19 publications

References 14 publications

Sketch-Based Image Matching Using Angular Partitioning

Sketch-Based Image Matching Using Angular Partitioning

Speeding up the similarity search in high-dimensional image database by multiscale filtering and dynamic programming

<title>Design and implementation of a concept-based image retrieval system with edge description templates</title>

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