• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• The Korean Journal of Pain
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• v.14 no.2
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• pp.156-163
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• 2001

Background: The categorical scales and visual analogue scales (VAS) are methods used for evaluating variations of postoperative pain intensity. Several studies have introduced the idea that there is a clear correlation between visual scales and categorical scales. However, when VAS is the only pain measure in the study, we do not know what point on the VAS represents a category on the categorical scale and their degree of correlation with satisfaction for postoperative pain. Methods: 252 patients who had undergone elective surgery were studied. A 5-point categorical scale (none, mild, moderate, severe, worst possible pain), a 0-100 mm VAS (no pain to worst possible pain) and patient satisfaction score were checked 24 hours after surgery using a pain questionnaire and VAS tool. Results: The mean VAS score of the 14 patients reporting 'no-pain' was $1.9{\pm}0.9$, $23.9{\pm}1.0$ for the 132 patients reporting 'mild-pain', $47.2{\pm}1.1$ for the 82 patients reporting 'moderate-pain' and $67.5{\pm}2.8$ for the 24 patients reporting 'severe-pain'. Of the patients reporting moderate pain, 85% scored over 45.6 mm on the corresponding VAS, with a mean score 47.2 mm. The mean satisfaction scores were $90.6{\pm}2.7$ for the 'no pain', patients, $75.1{\pm}1.3$ for ‘mild pain', $58.3{\pm}1.5$ for 'moderate pain', and $55.1{\pm}4.0$ for 'severe pain' patients. The categorical scale was significantly correlated with VAS (P < 0.01). The satisfaction score was significantly inversely correlated with VAS (P < 0.01). Conclusions: Our results indicate that if a patient records a VAS score in excess of 45.6 mm they would probably have recorded at least moderate pain on a 5-point categorical scale. The categorical scale can be used properly for postoperative pain measurement with VAS. More research is required for the development of suitable pain descriptor for a categorical scale and pain questionnaire in Korean.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.1-10
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• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3997-4001
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• 2016

Background: Cancer is a worldwide health problem and pain is among the most common and unpleasant effects affecting well-being of cancer patients. Accurate description of pain can help physicians to improve its management. Many English tools have been developed to assess pain. Onkly a limited number of these are applied in Arab countries. Our aim was to assess the quality, the nature and the severity of pain using the short McGill Pain Questionnaire (SF-MPQ) on cancer patients in the National Institute of Oncology (NIO) in Rabat, Morocco. Materials and Methods: The tool used is the SF-MPQ inspired from the Arabic version of the MPQ. The subjects were cancer patients (N=182) attending the NIO, from 24th October 2015 to 8th January 2016, aging ${\geq}18$ years old, experiencing pain and coming to have or to update their pain medication. Results: The rate of participation was 96.3%. Eight patients had difficulties to express their pain using descriptors, but could use the Visual Analogue Scale (VAS) and the body diagram. The most frequent sensory descriptors were 'Throbbing', 'Shooting', 'Hot-Burning'. The most used affective descriptor was 'Tiring-Exhausting'. The mean VAS was 6.6 (2.4). The mean score of all items was 11.9 (7.8). The patients were suffering from severe pain. The internal consistency of the form was s acceptable. Conclusions: The findings indicate that most of the patients attending the pain center of the NIO could use the descriptors of the SF-MPQ to describe their pain. They indicate the usefulness of the SF-MPQ to assess the nature and the severity of pain in cancer patients. This tool should be tested in other Moroccan and Arabic contexts associated with other tools in clinical trials.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.51-61
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• 2017

This paper proposes a method to generate panoramic images by combining conventional feature extraction algorithms (e.g., SIFT, SURF, MPEG-7 CDVS) with sensed data from an inertia sensor to enhance the stitching results. The challenge of image stitching increases when the images are taken from two different mobile phones with no posture calibration. Using inertia sensor data obtained by the mobile phone, images with different yaw angles, pitch angles, roll angles are preprocessed and adjusted before performing stitching process. Performance of stitching (e.g., feature extraction time, inlier point numbers, stitching accuracy) between conventional feature extraction algorithms is reported along with the stitching performance with/without using the inertia sensor data.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.117-128
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• 2011

In this paper, we present a novel approach for contents-based medication image retrieval from a medication image database using the shape classification and color information of the medication. One major problem in developing a contents-based drug image retrieval system is there are too many similar images in shape and color and it makes difficult to identify any specific medication by a single feature of the drug image. To resolve such difficulty in identifying images, we propose a hybrid approach to retrieve a medication image based on shape and color features of the medication. In the first phase of the proposed method we classify the medications by shape of the images. In the second phase, we identify them by color matching between a query image and preclassified images in the first phase. For the shape classification, the shape signature, which is unique shape descriptor of the medication, is extracted from the boundary of the medication. Once images are classified by the shape signature, Hue and Saturation(HS) color model is used to retrieve a most similarly matched medication image from the classified database images with the query image. The proposed system is designed and developed especially for specific population- seniors to browse medication images by using visual information of the medication in a feasible fashion. The experiment shows the proposed automatic image retrieval system is reliable and convenient to identify the medication images.

• The Transactions of the Korea Information Processing Society
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• v.5 no.12
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• pp.3025-3035
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• 1998

In this paper, we describe the design and implementationof COIRS COncept,based Image Retricval System). It differs from extant content-based image retrieval systems in that it enables users to query based on concepts- it allows users to get images concepmally relevant. A concept is basically an aggregation of promitive objects in an image. For such a cencept based image retrieval functionality. COIRS aglopts an image descriptor called triple and includes a triple thesaurus used for capturing concepts. There are four facilities in COIRS: a visual image indeses a triple thesaurus, an inverted fiel, and a user query interface. The visnal image indeser facilitates object laeling and the percification of positionof objects. It is an assistant tool designed to minimize manual work when indexing images. The thesarrus captires the concepts by analyzing triples, thereby extracting image semantics. The triples are then for formalating queries as well as indexing images. The user query interiare enables users to formulate...