• Journal of Korea Multimedia Society
• /
• v.7 no.10
• /
• pp.1378-1388
• /
• 2004

This paper proposes method to improve the image quality degradation that show when reconstructing compressed images at low bit rate by using wavelet transform. The image quality distortion is blocking artifacts and noise in DCT's compression but blocking artifacts of wavelet transform does not appear and ringing artifacts was appeared near the edge. This proposed technique is classified to part which is ringing artifacts of the edge vicinity appears which is not, apply adaptive filter to each region improved image. A edge region which is harsh to the eye is applied by Canny mask and finding strong edge region, search the neighborhood classify the flat region and the texture region, and apply to each region suitable filter, As experiment result, PSNR value of method that is proposed in that low bit rate compression image that ringing artifact appears became low about 0.05db, but 0.023db degree rose strong edge region and nat region's image. Also, showed picture quality improved more than ringing artifacts in nat region when see from subjective viewpoint of human.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.7 no.4
• /
• pp.205-211
• /
• 2014

This paper addresses the framework of object-oriented image coding, describing a new algorithm, based on monodimensional Legendre polynomials, for texture approximation. Through the use of 1D orthogonal basis functions, the computational complexity which usually makes prohibitive most of 2D region-oriented approaches is significantly reduced, while only a slight increment of distortion is introduced. In the aim of preserving the bidimensional intersample correlation of the texture information as much as possible, suitable pseudo-bidimensional basis functions have been used, yielding significant improvements with respect to the straightforward 1D approach. The algorithm has been experimented for coding still images as well as motion compensated sequences, showing interesting possibilities of application for very low bitrate video coding.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.5
• /
• pp.133-138
• /
• 2010

In this paper, we make up a feature image including spatial properties and statistical properties on image, and format covariance matrices using region variance magnitudes. By using it to texture classification, this paper puts a proposal for tough texture classification way to illumination, noise and rotation. Also we offer a way to minimalize performance time of texture classification using integral image expressing middle image for fast calculation of region sum. To estimate performance evaluation of proposed way, this paper use a Brodatz texture image, and so conduct a noise addition and histogram specification and create rotation image. And then we conduct an experiment and get better performance over 96%.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.7
• /
• pp.2400-2419
• /
• 2014

Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.

• Journal of the Institute of Convergence Signal Processing
• /
• v.11 no.3
• /
• pp.215-220
• /
• 2010

In this paper, we propose a new texture-based page segmentation and classification method in which table region, background region, image region and text region in a given document image are automatically identified. The proposed method for document images consists of two stages, document segmentation and contents classification. In the first stage, we segment the document image, and then, we classify contents of document in the second stage. The proposed classification method is based on a texture analysis. Each contents in the document are considered as regions with different textures. Thus the problem of classification contents of document can be posed as a texture segmentation and analysis problem. Two-dimensional Gabor filters are used to extract texture features for each of these regions. Our method does not assume any a priori knowledge about content or language of the document. As we can see experiment results, our method gives good performance in document segmentation and contents classification. The proposed system is expected to apply such as multimedia data searching, real-time image processing.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.9
• /
• pp.1369-1373
• /
• 2015

Curve subdivision interpolation reconstructs edge well with low complexity, however it lacks of ability to recover texture components, instead. While, neighbor embedding is superior in texture reconstruction. Therefore, in this paper, a novel Super Resolution technique which combines curve subdivision interpolation and neighbor embedding is proposed. First, edge region and non-edge regions are classified. Then, for edge region, the curve subdivision algorithm is used to make two polynomials derived from discrete pixels and adaptive weights are adapted for gradients of 4 different sides to make smooth edge. For non edge region, neighbor-embedding method is used to conserve texture property in original image. Consequently results show that the proposed technique conserves sharp edges and details in texture better, simultaneously.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2001.11a
• /
• pp.55-62
• /
• 2001

An electrolytic copper rod was drawn up to $90\%$ in area reduction and annealed under various conditions. The EBSD measurement of the drawn wire showed that in the center region the <111> + <100> fiber duplex texture was dominant, while in the middle and surface regions relatively defused textures developed with a little higher density in <11w>//wire axis. The inhomogeneous texture in the deformed wire gave rise to the inhomogeneous microstructure and texture after annealing. The annealing texture could be classified into the recrystallization texture developed during low temperatures and at the early stage at a high temperature and the growth texture developed after a prolonged annealing at the high temperature. The recrystallization temperature could be explained by the strain energy release maximization model and the growth texture was discussed based on the grain boundary mobility anisotropy.

• Transactions of Materials Processing
• /
• v.7 no.5
• /
• pp.459-464
• /
• 1998

Effect of the several initial textures such as random texture, rolling texture and cube texture, on the plane strain stretching was studied by interpretation of the finite element method. The calculation of yield locus indicated that the sheet oriented in the cube texture exhibits easy yielding on uniaxial stress state whereas the sheet having either a random or the rolling texture exhibits easy yielding on shear deformation. Upon stretching tests, the thickness strain at the center region contacting the punch was identical regardless of the initial textures while the dependence of the thickness strain on the initial texture was found in the other regions. In general punch loads required or the sheet with an initial cube texture was as expected from calculated yield locus, lower than those for the others.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.1
• /
• pp.97-102
• /
• 2013

Objective: The aim of this study was to develop an automated computer-aided diagnostic system for diagnosis of thyroid cancer pattern in fine needle aspiration cytology (FNAC) microscopic images with high degree of sensitivity and specificity using statistical texture features and a Support Vector Machine classifier (SVM). Materials and Methods: A training set of 40 benign and 40 malignant FNAC images and a testing set of 10 benign and 20 malignant FNAC images were used to perform the diagnosis of thyroid cancer. Initially, segmentation of region of interest (ROI) was performed by region-based morphology segmentation. The developed diagnostic system utilized statistical texture features derived from the segmented images using a Gabor filter bank at various wavelengths and angles. Finally, the SVM was used as a machine learning algorithm to identify benign and malignant states of thyroid nodules. Results: The SVMachieved a diagnostic accuracy of 96.7% with sensitivity and specificity of 95% and 100%, respectively, at a wavelength of 4 and an angle of 45. Conclusion: The results show that the diagnosis of thyroid cancer in FNAC images can be effectively performed using statistical texture information derived with Gabor filters in association with an SVM.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.6
• /
• pp.89-96
• /
• 1989

An improved method on texture coding, which is a part of the region growing based image coding, is presented in this paper. An image is segmented into stochastic regions which can be described as a stochastic random field, and non-stochastic ones in order to efficiently represent texture. In the texture coding and reconstruction, an autoregressive model is used for the stochastic regions, while a two-dimensional polynomial approximation is used for the non-stochastic ones. This proposed method leads to a better subjective quality, relatively higher compression ratio and shorter processing time for coding and reconstructing than the conventional method which uses only two-dimensional polynomial approximation.