• Applied Microscopy
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• v.44 no.2
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• pp.41-46
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• 2014

In this study, the vegetative and reproductive morphology and anatomy of two Hawaiian endemic Portulaca species were examined. Specifically, P. molokiniensis and P. sclerocarpa were compared to closely related species in the genus. The comparisons were both qualitative and quantitative, using characteristics of leaves, stems, roots, and fruits. Tissue organizations of vegetative and reproductive parts of the plants were assessed using microtechnique procedures, statistical analysis, and scanning electron microscopy. The most notable features of these two species were (1) the size and frequency of stomata in P. molokiniensis, and (2) the large number of sclerenchymatous cell layers in the thickest fruit walls of P. sclerocarpa. These findings may imply that stomata development in P. molokiniensis and thick fruit wall development in P. sclerocarpa are evolved features of survival. In particular, the development of thickened walls in indehiscent fruits likely has evolutionary implications of ecological tolerance for better adaptation.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.317-319
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• 2022

Rich morphology language such as Arabic needs more investigation and method to improve the sentiment analysis task. Using all document parts in the process of the sentiment analysis may add some unnecessary information to the classifier. Therefore, this paper shows the ongoing work to use sentence location as a feature with Arabic sentiment analysis. Our proposed method employs a supervised sentiment classification method by enriching the feature space model with some information from the document. The experiments and evaluations that were conducted in this work show that our proposed feature in the sentiment analysis for Arabic improves the performance of the classifier compared to the baseline model.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.248-255
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• 2014

In this paper, we propose a pothole detection method in asphalt pavement using various features. Segmentation, candidate, and decision steps of pothole detection are processed according to the values which are derived from feature characteristics. Segmentation step, we use histogram and closing operation of morphology filter which extracts dark regions for pothole detection. Candidate step, we extract candidate regions of pothole using various features such as size, compactness, etc. Finally, decision step, candidate regions are decided whether pothole or not using comparison of pothole and background's features. Experimental results show that our proposed pothole detection method has better results than existing methods and good performance in discrimination of pothole and similar patterns.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.53-62
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• 2007

In this paper, it can propose that Fuzzy Wavelet Morphology Neural Networks for the edge detection algorithm with being robustly a unclear boundary parts by brightness difference and being less sensitivity on direction to be detected the edges of images. This is applying the Fuzzy Wavelet Morphology Operator which can be simple the image robustly without the loss of data to DTCNN Structure for improving defect which carrys out a lot of operation complexly. Also, this color image can segment Y image with YCbCr space color model which has a lossless feature information of edge boundary sides effectively. This paper can offer the simulation of color images of 50ea for the performance verification of the proposal algorithm.

• Polymer(Korea)
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• v.24 no.3
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• pp.366-373
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• 2000

In this study, the PPS/ABS blend system was investigated in order to collectively identify the relationship among blend morphology, chemical compatibilization and thermal property. ABS resin was chemically modified by the incorporation of maleic anhydride through reactive extrusion for enhanced compatibilization, and PPS, ABS and the modified ABS were blend by a sing twin screw extruder. The effect of chemical modification of ABS on the morphological, mechanical, and thermal properities of the resulting blend was examined. A strong interaction was observed between PPS and MABS by optical microsopy as well as scanning electron microscopy, exhibiting a well-dispersed morphological feature. The PPS/MABS blend showing a single glass transition temperature was observed in dynamic mechanical analysis, demonstrating a pseudo-homogeneous phase morphology induced by chemical compatibilization. PPS/MABS blend also exhibited an enhanced thermal stability and heat distortion temperature compared with modified PPS/ABS blend.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.359-364
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• 2014

In this paper, we propose a method for extracting a road area by using the mean-shift method and connected-component method. Mean-shift method is very effective to divide the color image by the method of non-parametric statistics to find the center mode. Generally, the feature points of road are extracted by using the information located in the middle and bottom of the road image. And it is possible to extract a road region by using this feature-point and the partitioned color image. However, if a road region is extracted with only the color information and the position information of a road image, it is possible to detect not only noise but also off-road regions. This paper proposes the method to determine the road region by eliminating the noise with the closing / opening operation of the morphology, and by extracting only the portion of the largest area using a connected-components method. The proposed method is simulated and verified by applying the captured road images.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.216-222
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• 2008

This paper proposed the multi characters detection algorithm using Color segmentation and the closing curve feature of LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of left and background color, etc. The proposed multi characters detection algorithm divided into three parts : The feature detection, characters format and characters detection Parts in order to be possible to apply to image of various feature. After preprocess that the new multi characters detection algorithm that proposed in this paper used wavelet, morphology, hough transform which is the synthesis logical model in order to raise detection rate by acquiring the non-perfection characters as well as the perfection characters with processing OR operation after processing each color area by AND operation sequentially. And the proposal algorithm is simulated with natural images which include natural character area regardless of size, resolution and slant and so on of image. And the proposal algorithm in this paper is confirmed to an excellent detection rate by compared with the conventional detection algorithm in same image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.38-43
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• 2008

Skin color information is an important feature for face region detection in color images. This can detect face region using statistical skin color model who is created from skin color information. However, due to the including of different race of people's skin color points, this general statistical model is not accurate enough to detect each specific image as we expected. This paper proposes method to detect correctly face region in various color image that other complexion part is included. In this method set face candidate region applying complexion Gausian distribution based on YCbCr skin color model and applied mathematical morphology to remove noise part and part except face region in color image. And achieved correct face region detection because using Haar-like feature. This approach is capable to distinguish face region from extremely similar skin colors, such as neck skin color or am skin color. Experimental results show that our method can effectively improve face detection results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.7-12
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• 2009

The new approach was proposed which uses feature extraction based on fuzzy integral in the process of face verification using morphological shape decomposition. The centre of area was used with image pixels related with structure element and its weight in an attempt to consider neighborhood information. Therefore the morphological operators were defined for feature extraction. And then the number of decomposition images were more about 4 times than the conventional. Finally in the simulations with the extractions for face verification it was proved that the approach in this paper was even more good than the conventional in stability of feature extraction and threshold value.