Image Retrieval of Songket Motifs Using Simple Shape Descriptors

Jamil, Nursuriati; Bakar, Zainab Abu; Sembok, Tengku Mohd Tengku

doi:10.1109/gmai.2006.29

Cited by 19 publications

(16 citation statements)

References 12 publications

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“…C. Shahabi and M. Safar, compare performance of boundary based methods for shape representation and retrieval: Fourier descriptors method FD (based on objects' shape radii), grid-based method GB (based on chain codes) in paper [10]. Combination of different percentages of five geometric shape descriptors are experimented by N. Jamil, et al in paper [11] . This paper experiments on the combinations of the Eccentricity, Rectangularity, Compactness, Convexity, Solidity.…”

Section: Related Workmentioning

confidence: 99%

Fish Shape Recognition using Multiple Shape Descriptors

Ghosh¹,

Mukherjee²,

Parekh³

2013

IJCA

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This paper studies recognition of fish shapes using both Region based and Contour based shape based descriptors [9]. Moment Invariants are chosen as the Region based descriptor and the Simple (geometric) shape descriptors (SSD) are used as Contour based shape descriptors. The shapes are varied through scaling and rotation. Manhattan Distance is used as the classifier. The study of the recognition rate by using moment invariants and simple shape descriptors is done separately. Each moment invariant (M1 , M2 , M3 , M4 and M5) is studied separately and jointly. Then simple shape descriptors are combined with moment invariants to get hybrid feature vectors for improving recognition rate.

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Section: Related Workmentioning

confidence: 99%

Fish Shape Recognition using Multiple Shape Descriptors

Ghosh¹,

Mukherjee²,

Parekh³

2013

IJCA

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“…Out of many geometric features that have been proposed by various authors~Jain, 1989; Sonka et al, 1999;Jamil et al, 2006;Russ, 2007;Sarfraz & Ridha, 2007!, it has been observed through our studies~Pattan et al, 2009, 2010a, 2010b! that the two geometric shape features, namely, diam-eter_ratio and area_ratio, provide better classification results.…”

Section: Feature Extractionmentioning

confidence: 99%

Fuzzy Rule Based Classification and Quantification of Graphite Inclusions from Microstructure Images of Cast Iron

Pattan

Mytri²,

Hiremath

2011

Microsc Microanal

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The quantification of three classes of graphite inclusions in cast iron, namely, nodular, flake, and irregular, is the most important process in the foundry industry. This classification is based on the ISO 945 proposed morphology of graphite inclusions. This work presents a novel solution for automatic quantitative analysis of graphite inclusions into the three mentioned classes. The proposed work comprises three stages, namely, preprocessing of micrographs, classification of graphite inclusions, and then quantification of inclusions in each class. An effort has been made in this work to propose a minimum set of features to represent graphite inclusion morphology. The method employs just two geometric shape descriptors: the diameter ratio and the area ratio. A fuzzy rule based classifier is built using known feature values that are efficient in the classification of the three classes of graphite inclusions. The proposed method is automatic, fast, and provides the basis for determining many more morphological parameters that can be determined with the least effort. The results obtained by the proposed method are compared with the manual method. It is observed that the results obtained from the proposed method are useful in the optimization of cast iron manufacturing in the foundry industry.

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“…Content-based image retrieval [6] field has been rather popular among researchers through a rapid study along with other popular research areas such as Database Management, Natural Language Processing, Signal Processing, Computer Vision, Network Systems and Human-Computer Interaction [7]. Since studies on the field of image retrieval have proliferated, the main issue is how to expect the user's preferences [8] to the result of the image obtained through the image retrieval system [9], [10], [11]. Various models of image feature extraction were introduced through the implementation of the development on a variety of retrieval systems.…”

Section: Introductionmentioning

confidence: 99%

“…The features mentioned are part of the basic content-based image retrieval technique. All these techniques can assist the process of near-duplicate image entirely, as evidenced by various studies that have been carried out [10], [12], [13], [14]. However, the techniques involved in www.ijacsa.thesai.org CBIR face obstacles in processing image datasets in highdimensional clusters [15], [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Visualising Image Data through Image Retrieval Concept using a Hybrid Technique: Songket Motif’s

Yusof¹,

Ismail²,

Majid³

2019

IJACSA

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It has been proven that the massive dataset is strictly complex in Content Based image Retrieval (CBIR) because the present strategies in CBIR might have faced difficulties in feature extraction of the images. Moreover, technological constraints encountered in the analysis and extraction of the image arrays are how the system customizes the primitive geometric structures known as polygonal approximations structure. Hence, this study has discovered that image feature extraction is utilized by applying the Principal Component Analysis (PCA) technique, which is primarily based on the matrix of image representation that will enlarge the similarity of detection. The PCA approach needs to be enhanced resulting from the lack of the extraction of features in songket motives images. Therefore, this study proposes a new hybrid model that will integrate PCA with geometric techniques for image feature extraction to increase the recall and precision result. This paper employs the use of a qualitative experimental design model that involves three phases of activities. First, the analysis and design phase, secondly is a development phase, and lastly is the testing and evaluation phase. This paper focuses on those two phases in terms of design and development phases. The outcome process of the empirical phase is followed by designing the algorithm and model based on the result of literature review. This study has found that the hybrid between the principal component analysis model and the geometry technique will help to reduce the problems faced by the basic engineering technique model, which is the constraint in analysing and extracting the image features to customize the geometric primitive structure.

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Image Retrieval of Songket Motifs Using Simple Shape Descriptors

Cited by 19 publications

References 12 publications

Fish Shape Recognition using Multiple Shape Descriptors

Fish Shape Recognition using Multiple Shape Descriptors

Fuzzy Rule Based Classification and Quantification of Graphite Inclusions from Microstructure Images of Cast Iron

Visualising Image Data through Image Retrieval Concept using a Hybrid Technique: Songket Motif’s

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