• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.132-134
• /
• 2004

Emotion recognition between human and human is done compositely using various features that are face, voice, gesture and etc. Among them, it is a face that emotion expression is revealed the most definitely. Human expresses and recognizes a emotion using complex and various features of the face. This paper proposes hybrid feature extraction for emotions recognition from facial expression. Hybrid feature extraction imitates emotion recognition system of human by combination of geometrical feature based extraction and color distributed histogram. That is, it can robustly perform emotion recognition by extracting many features of facial expression.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.55.2-55
• /
• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region efface candidate. The feature information in the region of face candidate is used to detect a face region. In the recognition step, as a tested, the 360 images of 30 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression, Input variables of the neural networks are the feature information that comes from the eigenface spaces. The simulation results of 30 persons show that the proposed method yields high recognition rates.

• ETRI Journal
• /
• 제41권4호
• /
• pp.483-493
• /
• 2019

Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권2호
• /
• pp.544-564
• /
• 2022

Underwater images often suffer from color distortion, blurring and low contrast, which is caused by the propagation of light in the underwater environment being affected by the two processes: absorption and scattering. To cope with the poor quality of underwater images, this paper proposes a multiscale fusion underwater image enhancement method based on channel attention mechanism and local binary pattern (LBP). The network consists of three modules: feature aggregation, image reconstruction and LBP enhancement. The feature aggregation module aggregates feature information at different scales of the image, and the image reconstruction module restores the output features to high-quality underwater images. The network also introduces channel attention mechanism to make the network pay more attention to the channels containing important information. The detail information is protected by real-time superposition with feature information. Experimental results demonstrate that the method in this paper produces results with correct colors and complete details, and outperforms existing methods in quantitative metrics.

• 복식
• /
• 제62권6호
• /
• pp.38-52
• /
• 2012

The purpose of this study is to confirm the international unique color sensibility according to the ethnic color preferences. The existing studies about color sensibility were investigated to analyze the international color sensibility. The countries were chosen according to its, strong regional and racial color. Also, the documents and websites about environment color such as structure color, natural feature color, traditional folk costume color and customary color names were investigated, and then, the international color sensibility was analyzed by using the color image scale. As a result of the analysis about the differences of color sensibility, internationally distinguished color sensibility was discovered. There were differences not only for the preference trend of hue but also for the tone or contrast of color among the selected countries. Especially, Great Britain had a strong preference for G categories that they preferred the warm-grayish color image. Russia has a preference for R, G, and B categories with the preference for the warm-clear image. Netherlands had a preference for R, Y, and PB categories and it preferred the cool-hard-grayish, warm-soft-clear image. Italy had a preference for R and Y categories and it preferred the warm-clear image. Morocco had a preference for R and B categories and it preferred the warm and cool, clear image. Japan had a preference for R, G categories and it preferred the warm-grayish image. Korea had a preference for R and B categories and it preferred the warm-soft-clear, and cool-clear image. With these results, the researcher concludes that the integrated analysis of the environment color and the traditional racial color factors are very persuasive methods to comprehend the international color sensibility.

• 한국실내디자인학회논문집
• /
• 제34호
• /
• pp.114-123
• /
• 2002

Koreans have regarded the red as a major color from old times. The red is a traditional color to have symbols of high position, national foundation and especially royalty. So, we can see the reds in the palace for kings very much.The purpose of this study is to draw out the features of color red in the Kyungbok palace. The color was analyzed by two categories-architectural buildings${\cdot}$structures and ornamental painted patterns. The major findings from this research are summarized as follows:1. Seokganju(similar to terra rossa) and toyugsaek(light seokganju) are found main colors in architectural space, while seokganju has a linear effect and toyuk has a facial effect. 2. Yugsaek(similar to light vermillion) and Jangdan(similar to orange) are found main colors in ornamental painted patterns. These colors are more vivid and brighter than those for architectural space.3. As for two-color combination, reds and blues(including greens) are found major combination both of architectural space and ornamental patterns. And reds and white are the following combination, which gives an bright image by white. 4. As for three-color combination, red-white-black combination of pediment and red-blue-white combination of openings are found very popular in architectural space, while red-blue-yellow combination is most popular in ornamental patterns.The reds are found dominant color of both architectural space and ornamental patterns in the Kyungbok palace. The color design as shown in the Kyungbok palace can be considered as the feature of traditional color design.

• IEIE Transactions on Smart Processing and Computing
• /
• 제6권4호
• /
• pp.229-236
• /
• 2017

This paper presents an efficient object-based color image-retrieval algorithm that is suitable for the classification and retrieval of images from small to mid-scale datasets, such as images in PCs, tablets, phones, and cameras. The proposed method first finds salient regions by using regional feature vectors, and also finds several dominant colors in each region. Then, each salient region is partitioned into small sub-blocks, which are assigned 1 or 0 with respect to the number of pixels corresponding to a dominant color in the sub-block. This gives a binary map for the dominant color, and this process is repeated for the predefined number of dominant colors. Finally, we have several binary maps, each of which corresponds to a dominant color in a salient region. Hence, the binary maps represent the spatial distribution of the dominant colors in the salient region, and the union (OR operation) of the maps can describe the approximate shapes of salient objects. Also proposed in this paper is a matching method that uses these binary maps and which needs very few computations, because most operations are binary. Experiments on widely used color image databases show that the proposed method performs better than state-of-the-art and previous color-based methods.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2016년도 추계학술발표대회
• /
• pp.510-513
• /
• 2016

Detecting of the object in image processing is substantial but it depends on the object itself and the environment. An object can be detected either by its shape or color. Color is an essential for pattern recognition and computer vision. It is an attractive feature because of its simplicity and its robustness to scale changes and to detect the positions of the object. Generally, color of an object depends on its characteristics of the perceiving eye and brain. Physically, objects can be said to have color because of the light leaving their surfaces. Here, we conducted experiment in the aquarium fish tank. Different color of fish robots are mimic the natural swim of fish. Unfortunately, in the underwater medium, the colors are modified by attenuation and difficult to identify the color for moving objects. We consider the fish motion as a moving object and coordinates are found at every instinct of the aquarium to detect the position of the fish robot using OpenCV color detection. In this paper, we proposed to identify the position of the fish robot by their color and use the position data to control the fish robot gathering in one point in the fish tank through serial communication using RF module. It was verified by the performance test of detecting the position of the fish robot.

• 산업경영시스템학회지
• /
• 제43권1호
• /
• pp.16-25
• /
• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.

• 한국지능시스템학회논문지
• /
• 제26권2호
• /
• pp.120-126
• /
• 2016

본 연구에서는 HCbCr 색 특징과 RBFNNs 패턴분류기를 이용하여 얼굴영상을 효과적으로 검출하고 인식하기 위한 방법에 대해 제안한다. 피부색을 검출하는 것은 계산이 빠르고 형태 변형에 강인하여 얼굴을 검출하기에 유용하지만 유사한 색을 갖는 다른 물체를 잘못 검출하기도 한다. 따라서 피부색 검출의 정확도를 높이기 위하여 HSI 색공간과 YCbCr 색공간으로부터 각각 H요소와 CbCr요소를 추출하고 이를 결합하는 방법을 제안하였다. 그리고 각각의 피부색 후보 영역에 대하여 Haar-like 특징을 사용하여 눈을 검출함으로써 얼굴의 정확한 위치를 찾아냈다. 마지막으로 제안된 FCM 기반 RBFNNs 패턴분류기를 이용하여 얼굴 인식을 수행하였다. 또 Cambridge ICPR 영상 DB에 대하여 제안된 방법의 모의실험을 수행하고 그 결과를 제시하였다.