The two volume set LNCS 6854/6855 constitutes the refereed proceedings of the International Conference on computer Analysis of Images and patterns, CAIP 2011, which took place in Seville, Spain, August 29-31, 2011. Th...
ISBN:
(数字)9783642236785
ISBN:
(纸本)9783642236778
The two volume set LNCS 6854/6855 constitutes the refereed proceedings of the International Conference on computer Analysis of Images and patterns, CAIP 2011, which took place in Seville, Spain, August 29-31, 2011. The 138 papers presented together with 2 invited talks were carefully reviewed and selected from 286 submissions. The papers are organized in topical section on: motion analysis, image and shape models, segmentation and grouping, shape recovery, kernel methods, medical imaging, structural patternrecognition, Biometrics, image and video processing, calibration; and tracking and stereo vision.
Purpose: To detect the defects during the high speed process of web printing, such as smudges, doctor streaks, pin holes, character misprints, foreign matters, hazing, wrinkles, etc., which are the main infecting fact...
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ISBN:
(纸本)9780819485809
Purpose: To detect the defects during the high speed process of web printing, such as smudges, doctor streaks, pin holes, character misprints, foreign matters, hazing, wrinkles, etc., which are the main infecting factors to the quality of printing presswork. Methods: A set of novel machine vision system is used to detect the defects. This system consists of distributed data processing with multiple linear cameras, effective anti-blooming illumination design and fast image processing algorithm with blob searching. Also, pattern matching adapted to paper tension and snake-moving are emphasized. Results: Experimental results verify the speed, reliability and accuracy of the proposed system, by which most of the main defects are inspected at real time under the speed of 300 m/min. Conclusions: High speed quality inspection of large-size web requires multiple linear cameras to construct distributed data processing system. Also material characters of the printings should also be stressed to design proper optical structure, so that tiny web defects can be inspected with variably angles of illumination.
This paper presents an improved feature extraction technique for the cursive characters recognition. This technique can be applied in the perspective of handwritten word recognition system based on segmentation. The b...
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This paper presents an improved feature extraction technique for the cursive characters recognition. This technique can be applied in the perspective of handwritten word recognition system based on segmentation. The bases of fused statistical features extraction technique are improved projection profile and transition features. To extend this principal, a technique is integrated with the projection profile information to detect shifts of background and foreground pixels in the image of a character. A classifier based on neural network is used to test the improved fused features and comparison is done with the projection profile (PP) and transition feature (TF) extraction techniques. By using standard dataset, PP and TF techniques altogether show best performance with fused features having new enhancements and the best results in the literature are compared promisingly with this technique. The characters that are taken from the CEDAR dataset show 91.38% recognition accuracy.
In this paper we present a new database suitable for both 2D and 3D face recognition based on photometric stereo, the so-called Photoface database. The Photoface database was collected using a custom-made four-source ...
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Soilless culture has been popular in modern agriculture. However, plants in soilless culture often appear to be nutrient deficient. Therefore the intellective diagnostic system of plants disease of nutrients deficienc...
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Soilless culture has been popular in modern agriculture. However, plants in soilless culture often appear to be nutrient deficient. Therefore the intellective diagnostic system of plants disease of nutrients deficiency is important. In this paper, a novel idea based on computervision is presented. Color and texture features of leaves are extracted by some methods such as percent intensity histogram, percent differential histogram, Fourier transform, and wavelet packet. Moreover, Genetic Algorithm (GA) has been used to select features to get the best information for diagnosing the disease. Experiments showed that the accuracy of this diagnostic system is above 82.5% and it can diagnose disease about 6-10 days before experts could determine. (C) 2011 Elsevier B.V. All rights reserved.
Emerging applications of computervision and patternrecognition in mobile devices and networked computing require the development of resource-limited algorithms. Linear classification techniques have an important rol...
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Emerging applications of computervision and patternrecognition in mobile devices and networked computing require the development of resource-limited algorithms. Linear classification techniques have an important role to play in this context, given their simplicity and low computational requirements. The paper reviews the state-of-the-art in gender classification, giving special attention to linear techniques and their relations. It discusses why linear techniques are not achieving competitive results and shows how to obtain state-of-the-art performances. Our work confirms previous results reporting very close classification accuracies for Support Vector Machines (SVMs) and boosting algorithms on single-database experiments. We have proven that Linear Discriminant Analysis on a linearly selected set of features also achieves similar accuracies. We perform cross-database experiments and prove that single database experiments were optimistically biased. If enough training data and computational resources are available, SVM's gender classifiers are superior to the rest. When computational resources are scarce but there is enough data, boosting or linear approaches are adequate. Finally, if training data and computational resources are very scarce, then the linear approach is the best choice.
We present a Bayes optimal framework to improve existing pattern classification methods. The idea is that we first derive a new space of representations where the Bayes error is potentially to be smaller, and then any...
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ISBN:
(纸本)9781601321916
We present a Bayes optimal framework to improve existing pattern classification methods. The idea is that we first derive a new space of representations where the Bayes error is potentially to be smaller, and then any classification approaches can be directly employed in this space to obtain higher classification accuracies. Extensive experiments with well-known classification approaches demonstrate the effectiveness of our framework in improving the classification performance.
Efficient location of fruits in the trees is the most important criterion of an automatic robotic harvesting system. The main challenges faced in the development of the robotic harvesting arm are accurate identificati...
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This book constitutes the refereed proceedings of the 4th International Conference on patternrecognition and Machine Intelligence, PReMI 2011, held in Moscow, Russia in June/July 2011. The 65 revised papers presented...
ISBN:
(数字)9783642217869
ISBN:
(纸本)9783642217852
This book constitutes the refereed proceedings of the 4th International Conference on patternrecognition and Machine Intelligence, PReMI 2011, held in Moscow, Russia in June/July 2011. The 65 revised papers presented together with 5 invited talks were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on patternrecognition and machine learning; image analysis; image and video information retrieval; natural language processing and text and data mining; watermarking, steganography and biometrics; soft computing and applications; clustering and network analysis; bio and chemo analysis; and document image processing.
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