This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine...
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ISBN:
(纸本)9781479923427
This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate steps during each iteration, the proposed algorithm can provide a good estimate of the accurate affine transformation in condition of poor initialization and lack of geometric assumptions on point sets. Some experiments about comparison with the current state-of-the art approaches, demonstrate the robustness and accuracy of our method.
Figs like other agricultural products may include cancerogenic aflatoxin which is caused by Aspergillus type molds. Under the UV illumination, a large portion of the aflatoxin contaminated figs expose Bright Greenish ...
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Figs like other agricultural products may include cancerogenic aflatoxin which is caused by Aspergillus type molds. Under the UV illumination, a large portion of the aflatoxin contaminated figs expose Bright Greenish Yellow Fluorescence (BGYF) in visible light spectrum. Using the fluorescence properties, the contaminated figs are visually detected and manually removed by workers. However, this procedure could not eliminate all the aflatoxin contaminated figs and the UV exposure may cause skin cancer on workers under UV illumination. Besides, the reflectance outside the visible spectrum may include significant information for aflatoxin contamination. In this study, we investigate the NIR reflectance spectroscopy for the detection of aflatoxin contaminated figs and correctly classified the figs with 90% mean accuracy.
作者：
Erdal YenialpHabil KalkanVision
Image Processing and Pattern Recognition Laboratory (VIPLAB) Bilgisayar Mühendisliği Bölümü Süleyman Demirel Üniversitesi Isparta Turkey
Segmentation algorithms are widely used in imageprocessing. These methods have different complexity values and the choice of reasonable methods decreases on large images. Especially on the medical images with large s...
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Segmentation algorithms are widely used in imageprocessing. These methods have different complexity values and the choice of reasonable methods decreases on large images. Especially on the medical images with large size, it may take days to perform segmentation in some methods. However, parallel implementation may eliminate the drawback of these algorithms to some extent. In this study, we propose to implement segmentation algorithms in parallel using Graphical processing Unit. Using the proposed implementation, the computation time of the K-centers, K-means and DBSCAN algorithms were decreases 87, 642 and 2 times, respectively.
Lines provide important information in images and line detection is crucial in many applications. Many line features can be used to detect line position while line width (i.e., thickness) is a more structured, higher-...
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ISBN:
(纸本)9781479900145
Lines provide important information in images and line detection is crucial in many applications. Many line features can be used to detect line position while line width (i.e., thickness) is a more structured, higher-level feature compared to edge or other line features. Every point of the wide line structure has its own width in spite of the structure's asymmetry. In this paper, we use the parallel edges to get the line orientation and width. We do not need to know the actual width of the line, but rather recover it to get the region of interest (ROI). Then use a modified OTSU obtaining proper region threshold T to segment the wide line structures. By fusing feature of width and gray, a sequence of tests has been conducted on a variety of image samples obtained from simple natural scene and our experimental results demonstrate the practical and robust of the proposed method.
Human action recognition is a hot topic in computer vision field. Various applicable approaches have been proposed to recognize different types of actions. However, the recognition performance deteriorates rapidly whe...
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ISBN:
(纸本)9781479923427
Human action recognition is a hot topic in computer vision field. Various applicable approaches have been proposed to recognize different types of actions. However, the recognition performance deteriorates rapidly when the viewpoint changes. Traditional approaches aim to address the problem by inductive transfer learning, in which target-view samples are manually labeled. In this paper, we present a novel approach for cross-view action recognition based on transduc-tive transfer learning. We address the problem by transferring instances across views. In our settings, both labels of examples from the target view and the corresponding relation between examples from pairwise views are dispensable. Experimental results on the IXMAS multi-view data set demonstrate the effectiveness of our approach, and are comparable to the state of the art.
Object classification in traffic scene surveillance has attracted much attention recent years. Traditional classification methods need lots of labeled samples to build a satisfying classifier. However, the acquisition...
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ISBN:
(纸本)9781479923427
Object classification in traffic scene surveillance has attracted much attention recent years. Traditional classification methods need lots of labeled samples to build a satisfying classifier. However, the acquisition of the labeled samples may cost lots of time and human labor. In this paper, we propose an label-propagation based semi-supervised learning method which uses the information of both labeled and unlabeled samples. Experiment results show that our method outperforms the traditional methods both in accuracy and robustness.
pattern matching is a fundamental application text retrieval, string query, biological sequence analysis, etc. Therefore, the effective algorithm performing this kind of matching is in great need. In this paper, the w...
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pattern matching is a fundamental application text retrieval, string query, biological sequence analysis, etc. Therefore, the effective algorithm performing this kind of matching is in great need. In this paper, the wildcard is defines to match any one character in a sequence. Multiple wildcards form a gap. The length of a flexible gap is arbitrary. We design CLPM algorithm by use of cross list index structure to realize pattern matching with flexible wildcard gaps. The preprocessing algorithm is designed to initialize cross list so as to reduce searching space. In CLPM algorithm, the effective intervals is defined and computed based on the start positions of each sub pattern in each string, which help to obtain matching result set. Moreover, the approximate pattern matching is converted to short extract pattern matching. The contrast experiments are done based on DBLP tile data set. The results show that CLMP algorithm has better performance in the same fields.
pattern Mining is a popular issue in biological sequence analysis. With the introduction of wildcard gaps, more interesting patterns can be mined. In this paper, we propose a new definition related to pattern frequenc...
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pattern Mining is a popular issue in biological sequence analysis. With the introduction of wildcard gaps, more interesting patterns can be mined. In this paper, we propose a new definition related to pattern frequency, under which the Apriori property holds. We define a pattern mining problem called Ming top-K Frequent patterns (MFP), where gaps are mined instead of specified. Compared with existing problems, MFP does not require any domain knowledge of the user. However, theoretical analysis and experimental results show that MFP favors inflexible patterns. We then define another problem where the flexibility threshold of each gap is specified by the user. The problem is called Mining top-K Frequent and Flexible patterns (MF 2 P). We develop algorithm with polynomial complexities for both problems. patterns can grow from both sides. Some interesting biological patterns mined by our algorithms are discussed.
image segmentation is the basis of imageprocessing and image analysis. However, there are no common method that can be used in natural images, and present methods fail to explain understandings of human's visual ...
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