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Many animal species exist in this world and there are always new species being discovered each year. Therefore, it is very important that these valuable species be documented properly to be referred to in future. Numerous information retrieval systems for managing and documenting animal species today only allow users to search animal images and descriptions online via text-based input. Therefore,...
This paper presents an automated computer vision system of shape defect detection for product quality inspection and monitoring system. Soft drink bottle is used as a tested product for the proposed system. The analysis framework includes data collection, pre-processing, morphological operation, feature extraction, and classification. Morphological operation technique is used to segment the image...
In this paper, we introduce a method to generate photos from sketches using Deep Convolutional Neural Networks (DCNN). This research proposes a method by combining a network to invert sketches into photos (sketch inversion net) with a network to predict color given grayscale images (colorization net). By using this method, the quality of generated photos is expected to be more similar to the actual...
This research describes skin disease recognition by using neural network which based on the texture analysis. There are many skin diseases which have a lot of similarities in their symptoms, such as Measles (rubeola), German measles (rubella), and Chickenpox etc. In general, these diseases have similarities in pattern of infection and symptoms such as redness and rash. Diagnosis and recognition of...
Segmentation process in an essential part in image processing to obtain good preparation either for further process of data mining or object recognition. This paper proposes a new method of segmenting tomato image for clustering its ripeness. The tomato images are taken from three types of smartphone camera in various lighting condition with white background. When taking picture by using smartphone...
In this work, the problem of video orchestration performed by combining information extracted by multiple video sequences is considered. The novelty of the proposed approach relies on the use of aesthetic features and of cinematographic composition rules for automatically aggregating the inputs from different cameras in a unique video. While prior methodologies have separately addressed the issues...
Person re-identification has received considerable attention in the image processing, computer vision and pattern recognition communities because of its huge potential for video-based surveillance applications and the challenges it presents due to illumination, pose and viewpoint changes among non-overlapping cameras. Being different from the widely used low-level descriptors, visual attributes (e...
Agricultural textures are in the interest of classification in image processing. Natural images have unique textural shapes inside which cause a tough problem for classification. This paper tests different feature extraction and classification approaches to serve a benchmarking on several agricultural databases like seeds and leaves. Features are obtained using Local Binary Pattern (LBP), Gray Level...
Monitoring phenology of agricultural plants is a critical understanding in precision agriculture. Vital improvements can be achieved with precise detection of phenological change of plants which would henceforth improve the timing for the harvest, pest control, yield prediction, farm monitoring, disaster warning etc. Many countries across the world have been developing initiatives to build national...
The overall aim of the proposed skin lesions classification method is to improve the quality and accuracy of existing skin diagnostic system by establishing superior feature extraction and classification of skin lesions from standard digital images. At first, images of skin lesions are pre-processed by resizing, removing hair, removing noise by filtering and enhancing contrast. Rather than using RGB/HSV/YCbCr...
Multimedia semantic concept detection is one of the major research topics in multimedia data analysis in recent years. Disaster information management needs the assistance of multimedia data analysis to better utilize those disasterrelated information, which has been widely shared by people through the Internet. In this paper, a Feature Affinity based Multiple Correspondence Analysis and Decision...
In this paper, we propose a pedestrian attribute recognition approach and a CNN-based person re-identification framework enhanced by pedestrian attributes. The knowledge of person attributes can help video surveillance tasks like person re-identification as well as person search, semantic video indexing and retrieval to overcome viewpoint changes with their robustness to the inherent visual appearance...
Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis or simply M. tuberculosis. It is primarily an infection of lungs, but it can also affect other parts of the body such as brain, intestine, kidney and spine. TB remains one of the leading cause of death in developing countries, although most are preventable if diagnosed early and treated. Among the available...
Color features extraction is one among methods widely used for mouth extraction. This relates to specific features possessed by mouth color compared to others facial components. Mouth has a strong chromatic color for red but weak for blue. Color features extraction produces colors that are used to generate a mouth map. This map is required for mouth extraction. Some previous researches on mouth extraction...
This paper proposes a novel suspected vehicle detection (SVD) system for detecting vehicles moving on roads without a license plate. To detect vehicles from a still image, a symmelet-based approach is derived to determine their ROIs without using any motion feature. A symmelet is a pair of an interest point and its corresponding symmetrical one. This paper modifies the non-symmetrical SURF descriptor...
Saliency detection in images attracts much research attention for its usage in numerous multimedia applications. In this paper, we propose a saliency detection method based on optimization for RGBD images. With RGBD images, our method utilizes the depth channel to enhance the identification of background and foreground regions. We firstly generate new depth image by using non-linear transformation...
The tracking and labeling of multiple objects in multiple cameras is a fundamental task in applications such as video surveillance, autonomous driving, and sports analysis. In an ad-hoc multi-camera network without a fusion center nodes can benefit from local cooperation to solve signal processing tasks, such as distributed image enhancement. A crucial first step for the successful cooperation of...
In Timor-Leste, the coffee is one of the most important product for the acquisition of foreign currency. However, there are almost no rationalizations, therefore, enhancing the value of the coffee efficiently at the local of production is desired. The final objective of our study is to develop the automatic coffee beans sorting system for the producers of coffee beans in Timor-Leste. As the first...
Monitoring techniques are a key technology for examining conditions in various scenarios (e.g., structural and weather conditions and disasters). The appropriate extraction of the features of these scenarios from observation data is important in understanding them. This study proposes a monitoring technique that allows sound environments to be expressed as a sound pattern. To this end, the concept...
To improve the performance of the computer-aided systems for breast cancer diagnosis, the ensemble classifier is proposed for classifying the histological structures in the breast cancer microscopic images into three region types: positive cancer cells, negative cancer cells and non-cancer cell (stromal cells and lymphocyte cells) image. The bagging and boosting ensemble techniques are used with the...
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