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A Framework for White Blood Cell Segmentation in Microscopic Blood Images Using Digital Image Processing

BIOLOGICAL PROCEDURES ONLINE 2009年第1期11卷 196-206页

作者： Sadeghian, Farnoosh Seman, Zainina Ramli, Abdul Rahman Kahar, Badrul Hisham Abdul Saripan, M-Iqbal Department of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Department of Pathology Faculty of Medicine and Health Sciences Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Sapura Secured Technologies Section 10 Wangsa Maju Kuala Lumpur Malaysia

Evaluation of blood smear is a commonly clinical test these days. Most of the time, the hematologists are interested on white blood cells (WBCs) only. Digital image processing techniques can help them in their analysis and diagnosis. For example, disease like acute leukemia is detected based on the amount and condition of the WBC. The main objective of this paper is to segment the WBC to its two dominant elements: nucleus and cytoplasm. The segmentation is conducted using a proposed segmentation framework that consists of an integration of several digital image processing algorithms. Twenty microscopic blood images were tested, and the proposed framework managed to obtain 92% accuracy for nucleus segmentation and 78% for cytoplasm segmentation. The results indicate that the proposed framework is able to extract the nucleus and cytoplasm region in a WBC image sample.

关键词： White blood cell segmentation Active contours snake algorithm Zack thresholding

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Automatic algorithm for Segmentation of Atherosclerotic Carotid Plaque

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JOURNAL OF STROKE & CEREBROVASCULAR DISEASES 2017年第2期26卷 411-416页

作者： Bonanno, Lilla Sottile, Fabrizio Ciurleo, Rosella Di Lorenzo, Giuseppe Bruschetta, Daniele Bramanti, Alessia Ascenti, Giorgio Bramanti, Placido Marino, Silvia IRCCS Ctr Neurolesi Bonino Pulejo SS 113Via Palermo I-98124 Messina Italy Univ Messina Dept Clin & Expt Med Messina Italy Univ Messina Dept Biomed & Dent Sci & Morphofunct Imaging Messina Italy

Background: Carotid atherosclerosis is one of the major causes of stroke. The determination of the intima-media thickness, the identification of carotid atherosclerotic plaque, and the classification of the different stenoses are considered as important parameters for the assessment of atherosclerotic diseases. The aim of this work is to segment the plaques and to allow a better comprehension of carotid atherosclerosis. Methods: We considered 44 subjects, 22 with and 22 without the presence of plaques in the carotid axis, and we applied the snake algorithm. Results: The resulting interclass correlation coefficients (ICCs) were significant for all 3 parameters (mean echogenicity: ICC1 = .78 [95% CI: .55-0.90];perimeter: ICC2 = .81 [95% CI: .61-0.92];area: ICC3 = .89 [95% CI: .75-0.95]). The diagnostic accuracy was 82%, with an appropriate cutoff value of 224.5, sensitivity of 79%, and specificity of 85%. Conclusions: In this study, we developed an automatic method to identify the carotid plaque. Our results showed that an automatic system of image segmentation could be used to identify, characterize, and measure atherosclerotic carotid plaques.

关键词： Automatic segmentation carotid atherosclerosis snake algorithm ultrasound image

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LED-Induced fluorescence and image analysis to detect stink bug damage in cotton bolls

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JOURNAL OF BIOLOGICAL ENGINEERING 2013年第1期7卷 1-10页

作者： Mustafic, Adnan Roberts, Erin E. Toews, Michael D. Haidekker, Mark A. Univ Georgia Coll Engn Athens GA 30602 USA Univ Georgia Dept Entomol Tifton GA 31793 USA

Background: Stink bugs represent a major agricultural pest complex attacking more than 200 wild and cultivated plants, including cotton in the southeastern US. Stink bug feeding on developing cotton bolls will cause boll abortion or lint staining and thus reduced yield and lint value. Current methods for stink bug detection involve manual harvesting and cracking open of a sizable number of immature cotton bolls for visual inspection. This process is cumbersome, time consuming, and requires a moderate level of experience to obtain accurate estimates. To improve detection of stink bug feeding, we present here a method based on fluorescent imaging and subsequent image analyses to determine the likelihood of stink bug damage in cotton bolls. Results: Damage to different structures of cotton bolls including lint and carpal wall can be observed under blue LED-induced fluorescence. Generally speaking, damaged regions fluoresce green, whereas non-damaged regions with chlorophyll fluoresce red. However, similar fluorescence emission is also observable on cotton bolls that have not been fed upon by stink bugs. Criteria based on fluorescent intensity and the size of the fluorescent spot allow to differentiate between true positives (fluorescent regions associated with stink bug feeding) and false positives (fluorescent regions due to other causes). We found a detection rates with two combined criteria of 87% for true-positive marks and of 8% for false-positive marks. Conclusions: The imaging technique presented herein gives rise to a possible detection apparatus where a cotton boll is imaged in the field and images processed by software. The unique fluorescent signature left by stink bugs can be used to determine with high probability if a cotton boll has been punctured by a stink bug. We believe this technique, when integrated in a suitable device, could be used for more accurate detection in the field and allow for more optimized application of pest control.

关键词： Fluorescent Mark Needle Puncture Cotton Boll Fluorescent Region snake algorithm

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Mobile target detection of intelligent surveillance system based on modified GVF

Mobile target detection of intelligent surveillance system b...

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4th International Conference on Computer Science and Education

作者： Zhou Jian-zhong Wang Shu-zong Naval Univ Engn Dept Weapon Engn Wuhan Peoples R China

ISBN: (纸本)9781424435197

the current methods of mobile target detection of video sequences have shortcomings such as poor disturbance-resistance and robustness. To solve this problem, an modified GVF snake algorithm was presented, new gradient vector field was founded which took full advantage of image gradient information, between-frame motion information and grey-level information of neighbor pixels. Simulation result indicates that this modified method can detect mobile target of video sequences efficiently, and improve the disturbance-resistance ability and robustness.

关键词： mobile target detection Gradient vector flow snake algorithm video sequences intelligent surveillance system

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Facial Spot Contour Extraction based on Color Image Processing 19

Facial Spot Contour Extraction based on Color Image Processi...

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4th International Conference on Biomedical Signal and Image Processing

作者： Liu, Xiaojin Sun, Jiuai Wang, Xiong Univ Shanghai Sci & Technol Sch Med Instrument & Food Engn Shanghai Peoples R China Shanghai Univ Med & Hlth Sci Sch Med Imaging Shanghai Peoples R China Shanghai Sixth Peoples Hosp East Hosp Dermatol Dept Shanghai Peoples R China

ISBN: (纸本)9781450372244

In this paper we discuss the problem of automatic contour extraction of facial spot based on RGB images. Prior similar work has been frequently used for processing those hyperpigmentation skin conditions such as melasma and melanoma, where the separation between pigmented area and normal skin is easy to define. However the melanin under facial spots is normally deposited in a scatter way and distributed superficially, this makes the contrast between the area of spots and that of normal skin become small. As such it is difficult to directly extract the contour of the spots. After analyzing the individual three color channels of facial spot RGB skin image, we found that the blue channel provides the clearest edge of the spots, while the edge presents a certain amount of blur in the red channel. Therefore, this study proposed a new image processing strategy for facial spots analysis, i.e. to firstly separate the RGB channels to obtain the blue channel, then, the maximum entropy threshold segmentation and the snake method are used to extract the contour of color spots. The experiments verified that the separated color channel and snake-based method can help to reliably extract edge contours and preserve the color information of the spot.

关键词： snake algorithm Edge detection Contour extraction Color image analysis White balance

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Image retrieval using by skin color and shape feature

Image retrieval using by skin color and shape feature

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International Conference on Computational Science and Its Applications (ICCSA 2007)

作者： Park, Jin-Young Kim, Gye-Young Choi, Hyung-Il Soongsil Univ Dept Media Grad Sch Seoul South Korea Soongsil Univ Dept Comp Grad Sch Seoul South Korea

In this paper, we propose a image retrieval method using skin color feature and shape feature. Section by using a method of snake, consider color information. Section II, image retrieval using by ICSS(Improve Curvatur... 详细信息

ISBN: (纸本)9783540744689

关键词： snake algorithm CSS(Curvature Scale Space) skin color distribution function similarity image retrieval

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Construction of a two-layer model for vehicle path planning and its solution by hybrid optimisation algorithm 5

Construction of a two-layer model for vehicle path planning ...

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5th International Conference on Computer Engineering and Application (ICCEA)

作者： Wang, Suxin Ning, Zhongbao Li, Yuhao Zhang, Jinkun Northeastern Univ Qinhuangdao Coll Control Engn Qinhuangdao Hebei Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9798350386783;9798350386776

In order to solve the vehicle path planning problem, a two-layer model of vehicle path planning and traffic flow distribution is constructed. The upper layer model is a vehicle path planning model based on multiple distribution centres, which calculates the vehicle path with the minimum total distribution time. The lower model is the traffic flow allocation model based on the principle of system optimality. The results obtained by the upper layer model will change the travelling data in the lower layer model, and the calculated data of the lower layer model will also affect the roadway travelling time in the upper layer model, so that more realistic path planning distribution paths can be obtained through the interaction relationship between the upper and lower layer models. In order to improve the convergence and distribution of the multi-objective optimisation algorithm, a hybrid jumping spider algorithm and snake algorithm are proposed. The validation results with examples show that the results obtained from the two-layer model are more in line with the real travelling situation and achieve the balance between distance and time.

关键词： vehicle path planning traffic flow assignment jumping spider algorithm snake algorithm

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Automatic Mosaicking Method for Large Block of Orthophotos

Automatic Mosaicking Method for Large Block of Orthophotos

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7th Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Parallel Processing of Images and Optimization and Medical Imaging Processing

作者： Ai Haibin Zhang Li Wang Lin Chinese Acad Surveying & Mapping Beijing 100830 Peoples R China

ISBN: (纸本)9780819485793

In order to mosaic neighboring and partly overlapping orthophotos of a scene into one large image, the paper proposes a large block orthophoto mosaicking method. In our method, seam lines firstly are delineated through overlap areas among orthophotos according to an optimal geometrical criterion. Then a network of mosaicking is built based on these delineated seam lines, and related topology information may be easily abstracted from the mosaicking network. In the second stage of our method, each seam line is optimized again by a modified snake algorithm. The algorithm makes every seam line meet the requirements of maximum color similarity of the images and maximum texture similarity. In order to searching an optimal seam line in a large overlap area as fast as possible, a hierarchical strategy is adapted. In that way, an optimized path through the overlap area is found, where the color and texture of the two images are similar. The still remaining jumps in hue and the differences in intensity and saturation have to be leveled by smooth interpolation in the vicinity of the seam line. After having processed all overlapping areas, a large block of orthophotos are automatically merged to a final large image.

关键词： orthophoto mosaic topology network snake algorithm seamline detection

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An active contour based SSD algorithm for tracking a moving object

An active contour based SSD algorithm for tracking a moving ...

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Conference on Real-Time Imaging VIII

作者： Han, Y Song, P Chung, H Hahn, H Soongsil Univ Sch Elect Engn Seoul 156743 South Korea

ISBN: (纸本)0819452009

Since the shape of a 3D object moving in 3D space changes a lot in 2D image due to translation and rotation, it is very difficult to track the object using the SSD algorithm which finds the matching object in the input image using the template of the moving object. To solve the problem, this paper presents an enhanced SSD algorithm which updates the template based on an extended snake algorithm adaptive to the shape variation. The proposed snake algorithm uses the derivative of the area as the constraint energy to determine the boundary of an interested area considering the progressive variation of the shape. The performance of the proposed algorithm has been proved by the experiments where a mobile robot with one camera tracks a 31) target object translating and rotating arbitrarily in the 3D workspace.

关键词： snake algorithm object tracking SSD algorithm mobile robot visual tracking

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Detection of runway boundary in ATC ground radar

Detection of runway boundary in ATC ground radar

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2010 IEEE Radar Conference

作者： Pierucci, Laura Bocchi, Leonardo Univ Florence Dept Elect & Telecommun I-50139 Florence Italy

ISBN: (纸本)9781424458127

The radar environment is usually nonstationary and an efficient adaptation requires real-time exploitation of a priori knowledge concerning the environment surrounding the radar. In an airport contest, the radar scenario is heavily influenced by the inevitable presence of interferences, the background clutter, but other interferences (presence of vehicles and unwanted signs on the runway) contribute to make difficult the target detection. In particular, the paper addresses the detection of the runway boundary in ATC (Air Traffic Control) ground radar signal which can be not well defined due to the grass growth in different period in the islands near the runways. The grass growth can cause critical situation because the signal level of the grass zones is equal to that of the asphalt and it needs a visual analysis by a human operator to determine the presence of objects and targets in this clutter area. An active contour search algorithm (snake algorithm) is used for detecting the runway boundary in SMR radar images. In our application a standard snake algorithm is adapted and it is possible to obtain a reasonable approximation of the actual contour, which greatly reduces drawbacks related to the presence of the local minima. The performance of the active contour algorithm is tested on a set of radar images extracted from SMR radar images acquired in Italian airports.

关键词： clutter detection snake algorithm active contour

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