Notice: Undefined index: linkPowrot in C:\wwwroot\wwwroot\publikacje\publikacje.php on line 1275
Publikacje
Pomoc (F2)
[77730] Rozdział:

Query-by-Shape Interface for Content Based Image Retrieval Based on Shape Analysis

w książce:   Human-Computer Systems Interaction
ISBN:  978-3-319-62119-7
Wydawca:  Springer
Opublikowano: 2018
Miejsce wydania:  Cham, Switzerland
Seria wydawnicza:  Advances in Intelligent Systems and Computing
Numer w serii wydawniczej:  551
Liczba stron:  11
Liczba arkuszy wydawniczych:  0.50
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Do oświadczenia
nr 3
Grupa
przynależności
Dyscyplina
naukowa
Procent
udziału
Liczba
punktów
do oceny pracownika
Liczba
punktów wg
kryteriów ewaluacji
Tomasz Michno orcid logo WEAiIKatedra Systemów Informatycznych *Niespoza "N" jednostkiAutomatyka, elektronika, elektrotechnika i technologie kosmiczne50.00.00  
Roman Stanisław Deniziak orcid logo WEAiIKatedra Systemów Informatycznych *Takzaliczony do "N"Automatyka, elektronika, elektrotechnika i technologie kosmiczne50.00.00  

Grupa MNiSW:  Autorstwo rozdziału w monografii naukowej w językach: angielskim, niemieckim, francuskim, hiszpańskim, rosyjskim lub włoskim
Punkty MNiSW: 0


Pełny tekstPełny tekst     DOI LogoDOI     Web of Science Logo Web of Science    
Słowa kluczowe:

CBIR  zapytania z użyciem kształtów  multimedialne bazy danych 


Keywords:

CBIR  query by approximate shapes  multimedia databases 



Abstract:

The paper presents a novel Content-Based Image Retrieval interface. The method decompose an object int a set of features. Each feature may consist of a colour, a texture or a shape with attributes representing additional information (e.g. a the type of material from which it is made). During the query process a graph of object is compared with graphs stored in the database. One of the main advantages of our approach is that there is no need of a full knowledge about the searched object. The interface which we propose allow users to draw a query with a defined set of basic shapes. Some users may also need objects which are not the same as searched object, therefore two results sets should be returned. The prototyped application written in Python and C++ was prepared in order to perform experiments.



B   I   B   L   I   O   G   R   A   F   I   A
[Aggarwal et al. 2002]
Aggarwal G, Ashwin T, Ghosal S (2002) An image retrieval system with automatic query modification. IEEE Transactions on Multimedia 4 (2): 201-214

[Bielecka and Skomorowski 2007]
Bielecka M, Skomorowski M (2007) Fuzzy-aided parsing for pattern recognition. In: Kurzynski M, Puchala E, Wozniak M, Zolnierek A (eds) Computer Recognition Systems 2, Advances in Soft Computing (45), Springer, Berlin Heidelberg, pp 313-318

[Cordella et al. 1998]
Cordella L, Foggia P, Sansone C, Tortorella F, Vento M (1998) Graph matching: a fast algorithm and its evaluation. In: Proc 14th Inter Conf on Pattern Recognition, Brisbane, Australia, pp 1582-1584

[Deniziak and Michno 2015]
Deniziak S, Michno T (2015) Query-by-shape interface for content based image retrieval. In: Proc IEEE 8th Inter Conf on Human System Interaction, Warsaw, Poland, pp 108–114

[Jakubowski 1985]
Jakubowski R (1985), Extraction of shape features for syntactic recognition of mechanical parts. IEEE Transactions on Systems, Man and Cybernetics SMC 15 (5):642-651

[Kato et al. 1992]
Kato T, Kurita T, Otsu N, Hirata K (1992) A sketch retrieval method for full color image database-query by visual example. In: Proc 11th Inter Conf on Pattern Recognition, Computer Vision and Applications I (A):530-533

[Kriegel et al. 2006]
Kriegel HP, Kroger P, Kunath P, Pryakhin A (2006) Effective similarity search in multimedia databases using multiple representations. In: Proc 12th Inter Multi-Media Modelling Conference, Beijing, China

[Lalos et al. 2008]
Lalos C, Doulamis A, Konstanteli K, Dellias P, Varvarigou T (2008) An innovative content-based indexing technique with linear response suitable for pervasive environments. In: Proc Inter Workshop on Content-Based Multimedia Indexing, London, UK, pp 462-469

[Lee and Fu 1983]
Lee HC, Fu KS (1983) Generating object descriptions for model retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI 5 (5):462-471

[Li and Hsu 2008]
Li CY, Hsu CT (2008) Image retrieval with relevance feedback based on graph-theoretic region correspondence estimation. IEEE Transactions on Multimedia 10 (3):447-456

[Mocofan et al. 2011]
Mocofan M, Ermalai I, Bucos M, Onita M, Dragulescu B (2011) Supervised tree content based search algorithm for multimedia image databases. In: Proc 6th IEEE International Symposium on Applied Computational Intelligence and Informatics, Timisoara, Romania, pp 469-472

[Shih 2002]
Shih TK (2002) Distributed multimedia databases. In: Shih TK (ed) Distributed multimedia databases, IGI Global, Hershey, PA, USA, pp 2-12

[Singh et al. 2012]
Singh A, Shekhar S, Jalal A (2012) Semantic based image retrieval using multi-agent model by searching and filtering replicated web images. In: Proc World Congress on Information and Communication Technologies, Trivandrum, India, pp 817-821

[Sluzek 2005]
Sluzek A (2005) On moment-based local operators for detecting image patterns. Image and Vision Computing 23 (3):287-298

[Ullmann 1976]
Ullmann JR (1976) An algorithm for subgraph isomorphism. J ACM 23(1):31-42

[Wang et al. 2010]
Wang HH, Mohamad D, Ismail NA (2010) Approaches, challenges and future direction of image retrieval. J Of Computing 2 (6)

[Zhuang and Wang 2010]
Zhuang D, Wang S (2010) Content-based image retrieval based on integrating region segmentation and relevance feedback. In: Proc Inter Conf on Multimedia Technology (ICMT), Ningbo, China, pp 1-3