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Manual inspection is commonly used to maintain the quality of light-emitting diode thin-film ceramic substrates. However, manual inspection has certain inherent and inevitable shortcomings. This paper describes an auto-inspection system for detecting defects on this type of integrated substrate surface using machine vision. A sequence of sub-images of an integrated substrate is grabbed and reconstructed...
This paper describes an efficient fire detection approach using color and texture information. Our approach consists of Fire Pixel Based Multi-rules Detection and Fire Texture Based Classification. We segment the fire candidate region in HIS and RGB color space using multi rules based on statistic color model, and then employ LBP to extract the fire texture features from those candidate regions. Finally,...
This paper presents a new SLAM (simultaneous localization and mapping) method using genetic algorithm (GA) for mobile robots. A laser range finder (LRF) is installed on a mobile robot for collecting point-distance information about the surroundings. From the LRF points, several important ones are extracted for describing the main features of the surroundings. A new form of chromosomes for representing...
In order to enhance security and protection capability, the integration of different biometric features to set up multimodal biometric authentication system is an effective way. It can provide complementary information to enhance recognition rate, and it can further enhance the reliability and stability of the identity authentication system. However, although the use of multimodal biometric feature...
Reliable recognition of activities from cluttered sensory data is challenging and important for a smart home to enable various activity-aware applications. In addition, understanding a user's preferences and then providing corresponding services is substantial in a smart home environment. Traditionally, activity recognition and preference learning were dealt with separately. In this work, we aim to...
In this paper, a liver diseases diagnosis based on Gabor wavelets and support vector machine (SVM) classifier is proposed. The diagnosis scheme includes two steps: features extraction and classification. The features derived from Gabor wavelets are obtained from the regions of interest (ROIs) among the normal and abnormal CT images. In the classification step, the SVM classifier is used to discriminate...
In this paper, a kernel-based classifier for automatic liver diseases diagnosis of CT images is introduced. Three kinds of liver diseases are identified including cyst, hepatoma and cavernous hemangioma. The diagnosis scheme includes two steps: features extraction and classification. The features, derived from gray levels, co-occurrence matrix, and shape descriptors, are obtained from the region of...
In this paper, a liver disease diagnosis based on Gabor filters is proposed. Three kinds of liver diseases are identified: cyst, hepatoma and cavernous hemangioma. The diagnosis scheme includes two steps: features extraction and classification. The features derived from Gabor filters are obtained from the ROIs among the normal and abnormal CT images. In the classification step the SVM classifier is...
This paper presents a vision-based geometric alignment system for aligning the projectors in an arbitrarily large display wall. Existing algorithms typically rely on a single camera view and degrade in accuracy as the display resolution exceeds the camera resolution by several orders of magnitude. Naive approaches to integrating multiple zoomed camera views fail since small errors in aligning adjacent...
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