Fuzzy Color Space for Apparel Coordination

Human perception of colors constitutes an important part in color theory. The applications of color science are truly omnipresent, and what impression colors make on human plays a vital role in them. In this paper, we offer the novel approach for color information representation and processing using fuzzy sets and logic theory, which is extremely useful in modeling human impressions. Specifically, we use fuzzy mathematics to partition the gamut of feasible colors in HSI color space based on standard linguistic tags. The proposed method can be useful in various image processing applications involving query processing. We demonstrate its effectivity in the implementation of a framework for the apparel online shopping coordination based on a color scheme. It deserves attention, since there is always some uncertainty inherent in the description of apparels

Towards a Universal Understanding of Color Harmony: Fuzzy Approach

Harmony level prediction is receiving increasing attention nowadays. Color plays a crucial role in affecting human aesthetic responses. In this paper, we explore color harmony using a fuzzy-based color model and address the question of its universality. For our experiments, we utilize a dataset containing attractive images from five different domains: fashion, art, nature, interior design, and brand logos. We aim to identify harmony patterns and dominant color palettes within these images using a fuzzy approach. It is well-suited for this task because it can handle the inherent subjectivity and contextual variability associated with aesthetics and color harmony evaluation. Our experimental results suggest that color harmony is largely universal. Additionally, our findings reveal that color harmony is not solely influenced by hue relationships on the color wheel but also by the saturation and intensity of colors. In palettes with high harmony levels, we observed a prevalent adherence to color wheel principles while maintaining moderate levels of saturation and intensity. These findings contribute to ongoing research on color harmony and its underlying principles, offering valuable insights for designers, artists, and researchers in the field of aesthetics.Comment: Submitted to FSDM 2023 - The 9th International Conference on Fuzzy Systems and Data Minin

Feature extraction method for clock drawing test

Recently, the number of elderly persons with dementia has been increasing. In the past, we proposed a dementia evaluation system using daily conversations and developed the system with a conversational robot. However, the current system is not ready for practical use because it can only evaluate time/geographical orientation and short-term memory, and some methods to evaluate other orientations and functions is required as well. In this paper, we discuss a new dementia evaluation system using not only daily conversations but also drawing tests. The authors employed a Clock Drawing Test (CDT) as a new dementia evaluation test and implemented it in a tablet device. This paper discusses a feature extraction and recognition method to distinguish normal cases from dementia cases. After evaluation experiments, the proposed method could recognize 87.6% of the clock drawing images

Extraction of Disease Area from Retinal Optical Coherence Tomography Images Using Three Dimensional Regional Statistics

AbstractWe propose a new extraction method of the macular disease area in the human retinal layer from OCT images using three dimensional regional statistics. In previous researches, we extracted disease area by using the mean and standard deviation of the two dimensional disease part pointed out by a clinical doctor. However, the previous method cannot extract disease area for some disease OCT images precisely. In this paper, we propose a new extraction method of the disease area using three dimensional regional statistics. We use a set of 128 images (3D-OCT image) consisted of 2 dimensional OCT retinal image about one retina of a patient. The regional mean and regional standard deviation of gray level are calculated in the three dimensional region of interest (ROI, 125 (=5 × 5 × 5) pixels) in the abnormal area pointed by a clinical doctor. These values are compared with every ROI in the abnormal area to extract the disease area, and the proposal system measures the volume of the disease area. We apply the proposed method to OCT images of 5 patients with retinal diseases. As a result, we can measure the volume of the abnormal area with 80.7% average accuracy

Dementia detection using weighted direction index histograms and SVM for clock drawing test

AbstractIncreasing the number of elderly persons who have dementia is one of the severe social problems. In Japan, the Ministry of Health, Labor and Welfare expects that the number of dementia patients will be around 5 million in 2025. It is also easily estimated that they require various living supports. Therefore, early detection and prevention of dementia are important. The authors have been developing a new system for quantitative and accurate evaluation of dementia. The basic concept of our system is evaluating a patient's dementia types and progression without awareness. To realize this, we are now developing the system using daily conversations, drawings, facial expressions and so on. In this paper, we focused on Clock Drawing Test (CDT) and proposed a dementia evaluation method for CDT. In the proposed method, Weighted Direction Index Histogram Method was used to extract features from given images, and Support Vector Machine (SVM) detected dementia cases from them. As a result of evaluation experiments, the proposed method could detect 97.1% of dementia cases correctly

A study on classification using machine learning for dementia evaluation

Recently, the number of dementia patients has been increasing due to the aging society. In Japan, a paper-based examination is the main-stream to measure the cognitive function of a subject, but these paper-based tests give much burden to not only patients but also evaluators like facility and medical staff. Therefore, it is necessary to develop a system that can automatically judge the degree of dementia progression, not to burden the doctor. Also, it is required to add play ability not to be a burden on the elderly. From this point of view, the authors developed a recreation game like a puzzle game. This system is easy to play for elderly people and is not a burden. Also, the question-answer is clear, so it is suitable for automatic judgment. We use the obtained features during recreation game to diagnose the degree of dementia progression. We committed the capability of machine learning techniques. Finally, we discussed that the collected features are sufficient to diagnose the degree of dementia progression

Near-Light Perspective Shape from Shading for 3D Visualizations in Endoscopy Systems

<p>Poster from:</p><p><br></p> <p>V. B. S. Prasath, H. Kawanaka. Near-light perspective shape from shading for 3D visualizations in endoscopy systems. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas, MO, USA, Nov 13-16, 2017.</p

Vascularization features for polyp localization in capsule endoscopy

<p>Poster from:</p> <p>V. B. S. Prasath, H. Kawanaka. Vascularization features for polyp localization in capsule endoscopy. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington D. C., USA, Nov 9-12, 2015.</p> <p> </p