Search results for: Content based image retrieval (CBIR)

Authors: Mario Mastriani, Marcelo Naiouf

Abstract:

The Gram-Schmidt Process (GSP) is used to convert a non-orthogonal basis (a set of linearly independent vectors) into an orthonormal basis (a set of orthogonal, unit-length vectors). The process consists of taking each vector and then subtracting the elements in common with the previous vectors. This paper introduces an Enhanced version of the Gram-Schmidt Process (EGSP) with inverse, which is useful for signal and image processing applications.

Keywords: Digital filters, digital signal and image processing, Gram-Schmidt Process, orthonormalization.

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Authors: Souvik Bhattacharyya, Gautam Sanyal

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In recent years, everything is trending toward digitalization and with the rapid development of the Internet technologies, digital media needs to be transmitted conveniently over the network. Attacks, misuse or unauthorized access of information is of great concern today which makes the protection of documents through digital media a priority problem. This urges us to devise new data hiding techniques to protect and secure the data of vital significance. In this respect, steganography often comes to the fore as a tool for hiding information. Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. It is of Greek origin and means "covered or hidden writing". The goal of steganography is covert communication. Here the carrier can be sent to a receiver without any one except the authenticated receiver only knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography. In this work the authors propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by selecting the embedding pixels using some mathematical function and then finds the 8 neighborhood of the each selected pixel and map each bit of the secret message in each of the neighbor pixel coordinate position in a specified manner. Before embedding a checking has been done to find out whether the selected pixel or its neighbor lies at the boundary of the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Keywords: Cover Image, LSB, Pixel Coordinate Position (PCP), Stego Image.

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Authors: K. Machida, H. Yamada

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Displacement measurement was conducted on compact normal and shear specimens made of acrylic homogeneous material subjected to mixed-mode loading by digital image correlation. The intelligent hybrid method proposed by Nishioka et al. was applied to the stress-strain analysis near the crack tip. The accuracy of stress-intensity factor at the free surface was discussed from the viewpoint of both the experiment and 3-D finite element analysis. The surface images before and after deformation were taken by a CMOS camera, and we developed the system which enabled the real time stress analysis based on digital image correlation and inverse problem analysis. The great portion of processing time of this system was spent on displacement analysis. Then, we tried improvement in speed of this portion. In the case of cracked body, it is also possible to evaluate fracture mechanics parameters such as the J integral, the strain energy release rate, and the stress-intensity factor of mixed-mode. The 9-points elliptic paraboloid approximation could not analyze the displacement of submicron order with high accuracy. The analysis accuracy of displacement was improved considerably by introducing the Newton-Raphson method in consideration of deformation of a subset. The stress-intensity factor was evaluated with high accuracy of less than 1% of the error.

Keywords: Digital image correlation, mixed mode, Newton-Raphson method, stress intensity factor.

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Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

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Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, depth estimation, deep neural networks, CNN

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Authors: Abhishek Neogi, Jayesh Verma, Pinaki Pratim Acharjya

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Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.

Keywords: Image segmentation, edge Detection, noisy images, spatialfilters, stochastic gradient kernel.

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Authors: Mohammad Akbarpour Sekeh, Mohd. Aizaini Maarof, Mohd. Foad Rohani, Malihe Motiei

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Duplicated region detection is a technical method to expose copy-paste forgeries on digital images. Copy-paste is one of the common types of forgeries to clone portion of an image in order to conceal or duplicate special object. In this type of forgery detection, extracting robust block feature and also high time complexity of matching step are two main open problems. This paper concentrates on computational time and proposes a local block matching algorithm based on block clustering to enhance time complexity. Time complexity of the proposed algorithm is formulated and effects of two parameter, block size and number of cluster, on efficiency of this algorithm are considered. The experimental results and mathematical analysis demonstrate this algorithm is more costeffective than lexicographically algorithms in time complexity issue when the image is complex.

Keywords: Copy-paste forgery detection, Duplicated region, Timecomplexity, Local block matching, Sequential block clustering.

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Authors: Hyunsup Yoon, Youngjoon Han, Hernsoo Hahn

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In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.

Keywords: Contrast Enhancement, Histogram Equalization, Histogram Region Equalization, Equalization Noise

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Authors: M. Chaoui, M-T. Laskri

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The evolution of information and communication technology has made a very powerful support for the improvement of online learning platforms in creation of courses. This paper presents a study that attempts to explore new web architecture for creating an adaptive online learning system to profiles of learners, using the Web as a source for the automatic creation of courses for the online training platform. This architecture will reduce the time and decrease the effort performed by the drafters of the current e-learning platform, and direct adaptation of the Web content will greatly enrich the quality of online training courses.

Keywords: Web Content, e-Learning, Educational Content, LMS, Profiles of Learners

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Authors: Maya S. Rathod, Bahadur Singh Hathan

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Mustard leaves are rich in folates, vitamin A, K and B-complex. Mustard greens are low in calories and fats and rich in dietary fiber. They are rich in potassium, manganese, iron, copper, calcium, magnesium and low in sodium. It is very rich in antioxidants and Phytonutrients. For the optimization of process variables (moisture content and mustard leave powder), the experiments were conducted according to central composite Face Centered Composite design of RSM. The mustard leaves powder was replaced with composite flour (a combination of rice, chickpea and corn in the ratio of 70:15:15). The extrudate was extruded in a twin screw extruder at a barrel temperature of 120°C. The independent variables were mustard leaves powder (2-10 %) and moisture content (12-20 %). Responses analyzed were bulk density, water solubility index, water absorption index, lateral expansion, antioxidant activity, total phenolic content, and overall acceptability. The optimum conditions obtained were 7.19 g mustard leaves powder in 100g premix having 16.8% moisture content (w.b).

Keywords: Extrusion, mustard leaves powder, optimization, response surface methodology.

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Authors: Abdul Raheem Jasim Mohammed, Mohd Salehuddin Mohd Zahari, Salim Abdul Talib, Mohd Zulhilmi Suhaimi

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The connection between past travel experience and tourists’ revisit behavioral intentions has not been widely explored but the existing studies suggest a close relationship between them. Destination image can equally be construed as having effects on the attitudes of the tourists at the end of their actual visitation and the satisfaction of a tourist with his or her travel experiences contributes to a revisit intention towards a particular destination. With strong marketing efforts, UAE is not only considered to be successful in attracting foreign investors, but is becoming the most popular tourism destination in the Arab region. UAE is seriously developing its tourism image and taking serious initiatives to attract new or repeat visitations from the international tourists. This study empirically investigates the causal relationships between tourism destination image, tourist satisfaction and revisit intention using UAE as a contextual study setting. A very clear picture emerged which provides a host country with potential implications for its tourism industry practitioners, Department of Tourism and Commerce Marketing and the travel agencies who act as the intermediaries between the potential tourists and the hotel operators.

Keywords: Destination image, tourist satisfaction, revisit intention.

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Authors: Zihan Yu, Kohei Inoue, Kiichi Urahama

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We present a method for dehazing images. A dark envelope image is derived with the bilateral minimum filter and a bright envelope is derived with the bilateral maximum filter. The ambient light and transmission of the scene are estimated from these two envelope images. An image without haze is reconstructed from the estimated ambient light and transmission.

Keywords: Image dehazing, bilateral minimum filter, bilateral maximum filter, local contrast.

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Authors: Ashish Thakur, Radhey Shyam Anand

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This paper presents the region based segmentation method for ultrasound images using local statistics. In this segmentation approach the homogeneous regions depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are to be extracted. This method uses a look up table comprising of the local statistics of every pixel, which are consisting of the homogeneity and similarity bounds according to the kernel size. The shape and size of the growing regions depend on this look up table entries. The algorithms are implemented by using connected seeded region growing procedure where each pixel is taken as seed point. The region merging after the region growing also suppresses the high frequency artifacts. The updated merged regions produce the output in formed of segmented image. This algorithm produces the results that are less sensitive to the pixel location and it also allows a segmentation of the accurate homogeneous regions.

Keywords: Local statistics, region growing, segmentation, ultrasound images.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

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In this paper, we present an improved fast and robust search algorithm for copy detection using histogram-based features for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal histogram feature which is robust to color distortion. Furthermore, by Combining with a temporal division method, the spatial and temporal features of the video sequence are integrated to realize fast and robust video search for copy detection. Experimental results show the proposed algorithm can detect the similar video clip more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Copy detection, Adjacent pixel intensity difference quantization (APIDQ), DC image, Histogram feature.

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Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

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Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: Ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear.

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Authors: Amr Almaddah, Sadi Vural, Yasushi Mae, Kenichi Ohara, Tatsuo Arai

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In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the training bootstrap by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe lighting conditions with significant improvements on the face recognition rates.

Keywords: Face synthesis and recognition, Face illumination recovery, 2D spherical spaces, Vision for graphics.

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Authors: Lun-Ping Hung, Nan-Chen Hsieh, Chia-Ling Ho, Chien-Liang Chen

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Currently, most of distance learning courses can only deliver standard material to students. Students receive course content passively which leads to the neglect of the goal of education – “to suit the teaching to the ability of students". Providing appropriate course content according to students- ability is the main goal of this paper. Except offering a series of conventional learning services, abundant information available, and instant message delivery, a complete online learning environment should be able to distinguish between students- ability and provide learning courses that best suit their ability. However, if a distance learning site contains well-designed course content and design but fails to provide adaptive courses, students will gradually loss their interests and confidence in learning and result in ineffective learning or discontinued learning. In this paper, an intelligent tutoring system is proposed and it consists of several modules working cooperatively in order to build an adaptive learning environment for distance education. The operation of the system is based on the result of Self-Organizing Map (SOM) to divide students into different groups according to their learning ability and learning interests and then provide them with suitable course content. Accordingly, the problem of information overload and internet traffic problem can be solved because the amount of traffic accessing the same content is reduced.

Keywords: Distance Learning, Intelligent Tutoring System(ITS), Self-Organizing Map (SOM)

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Authors: Leili Nosrati, Alireza Nemaney Pour

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Although e-mail is the most efficient and popular communication method, unwanted and mass unsolicited e-mails, also called spam mail, endanger the existence of the mail system. This paper proposes a new algorithm called Dynamic Weighted Majority Concept Drift Detection (DWM-CDD) for content-based filtering. The design purposes of DWM-CDD are first to accurate the performance of the previously proposed algorithms, and second to speed up the time to construct the model. The results show that DWM-CDD can detect both sudden and gradual changes quickly and accurately. Moreover, the time needed for model construction is less than previously proposed algorithms.

Keywords: Concept drift, Content-based filtering, E-mail, Spammail.

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Authors: Sijie Fu, Pascal-Henry Biwolé, Christian Mathis

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Among modern airflow measurement methods, Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV), as visualized and non-instructive measurement techniques, are playing more important role. This paper conducts a comparative experimental study for airflow measurement employing both techniques with the same condition. Velocity vector fields, velocity contour fields, voticity profiles and turbulence profiles are selected as the comparison indexes. The results show that the performance of both PIV and PTV techniques for airflow measurement is satisfied, but some differences between the both techniques are existed, it suggests that selecting the measurement technique should be based on a comprehensive consideration.

Keywords: PIV, PTV, airflow measurement.

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Authors: Min Li, Tao Li

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This paper constructs a four factors theoretical model of Chinese small and medium enterprises based on the “cartoon characters- reputation - enterprise marketing and management capabilities – protection of the cartoon image - institutional environment" by literature research, case studies and investigation. The empirical study show that the greatest impact on current merchandising rights income is the institutional environment friendliness, followed by marketing and management capabilities, input of character image protection and Cartoon characters- reputation through the real-time grey relational analysis, and the greatest impact on post-merchandising rights profit is Cartoon characters reputation, followed by the institutional environment friendliness, then marketing and management ability and input of character image protection through the time-delay grey relational analysis.

Keywords: Cartoon characters, merchandising rights, influencefactors, grey relational analysis

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Authors: Jedol Dayou, Jackson Hian Wui Chang, Rubena Yusoff, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Justin Sentian

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Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.

Keywords: Aerosol optical depth, direct normal irradiance, Langley calibration, radiance-based validation, SMARTS.

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Authors: Nandini N., Srikanta Murthy K., G. Hemantha Kumar

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This paper includes two novel techniques for skew estimation of binary document images. These algorithms are based on connected component analysis and Hough transform. Both these methods focus on reducing the amount of input data provided to Hough transform. In the first method, referred as word centroid approach, the centroids of selected words are used for skew detection. In the second method, referred as dilate & thin approach, the selected characters are blocked and dilated to get word blocks and later thinning is applied. The final image fed to Hough transform has the thinned coordinates of word blocks in the image. The methods have been successful in reducing the computational complexity of Hough transform based skew estimation algorithms. Promising experimental results are also provided to prove the effectiveness of the proposed methods.

Keywords: Dilation, Document processing, Hough transform, Optical Character Recognition, Skew estimation, and Thinning.

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Authors: K. Amudha, C. Nelson Kennedy Babu, S. Balu

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The security of the medical images and its related data is the major research area which is to be concentrated in today’s era. Security in the medical image indicates that the physician may hide patients’ related data in the medical image and transfer it safely to a defined location using reversible watermarking. Many reversible watermarking methods had proposed over the decade. This paper enhances the security level in brain tumor images to hide the patient’s detail, which has to be conferred with other physician’s suggestions. The details or the information will be hidden in Non-ROI area of the image by using the block cipher algorithm. The block cipher uses different keys to extract the details that are difficult for the intruder to detect all the keys and to spot the details, which are the key advantage of this method. The ROI is the tumor area and Non-ROI is the area rest of ROI. The Non-ROI should not be spoiled in any cause and the details in the Non-ROI should be extracted correctly. The reversible watermarking method proposed in this paper performs well when compared to existing methods in the process of extraction of an original image and providing information security.

Keywords: Brain tumor images, Block Cipher, Reversible watermarking, ROI.

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Authors: Wan Nural Jawahir Wan Yussof, Hans Burkhardt

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Liver segmentation is the first significant process for liver diagnosis of the Computed Tomography. It segments the liver structure from other abdominal organs. Sophisticated filtering techniques are indispensable for a proper segmentation. In this paper, we employ a 3D anisotropic diffusion as a preprocessing step. While removing image noise, this technique preserve the significant parts of the image, typically edges, lines or other details that are important for the interpretation of the image. The segmentation task is done by using thresholding with automatic threshold values selection and finally the false liver region is eliminated using 3D connected component. The result shows that by employing the 3D anisotropic filtering, better liver segmentation results could be achieved eventhough simple segmentation technique is used.

Keywords: 3D Anisotropic Diffusion, non-linear filtering, CT Liver.

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Authors: Ilze Gramatina, Laima Silina, Tatjana Rakcejeva

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Venison is well known as a traditional meat type in Europe and it is lower in calories, cholesterol and fat content than common cuts of beef, pork or lamb. The aim of the current research was to determine content of amino acids (LVS ISO 13903:2005) in different types of marinades marinated venison during storage. Beef as a control was analyzed for comparison of obtained results. The meat (2x3x2cm) pieces were marinated in two different types of marinades: red wine and tomato sauce marinade. The prepared meat samples were stored (marinated) at 4±2ºC temperature for 48±1h. Marinated meat was placed in polypropylene trays, hermetically sealed with high barrier polymer film under modified atmosphere (C0₂ 40%+N₂ 60%) without and with iron based oxygen scavenger sachets (Mitsubishi Gas Chemical Europe Ageless®), all samples were compared with packed marinated products in air ambiance. Results of current research show that changes of amino acids content in marinated venison mainly depend on packaging conditions.

Keywords: Marinated venison, modified atmospheres, oxygen absorber.

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Authors: John N. Ellinas

Abstract:

In this paper, a new reversible watermarking method is presented that reduces the size of a stereoscopic image sequence while keeping its content visible. The proposed technique embeds the residuals of the right frames to the corresponding frames of the left sequence, halving the total capacity. The residual frames may result in after a disparity compensated procedure between the two video streams or by a joint motion and disparity compensation. The residuals are usually lossy compressed before embedding because of the limited embedding capacity of the left frames. The watermarked frames are visible at a high quality and at any instant the stereoscopic video may be recovered by an inverse process. In fact, the left frames may be exactly recovered whereas the right ones are slightly distorted as the residuals are not embedded intact. The employed embedding method reorders the left frame into an array of consecutive pixel pairs and embeds a number of bits according to their intensity difference. In this way, it hides a number of bits in intensity smooth areas and most of the data in textured areas where resulting distortions are less visible. The experimental evaluation demonstrates that the proposed scheme is quite effective.

Keywords: Stereoscopic video, Reversible watermarking, Disparity compensation, Joint compensation

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Authors: Ali Alzaabi, Georges Alquié, Hussain Tassadaq, Ali Seba

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This article presents the developments of efficient algorithms for tablet copies comparison. Image recognition has specialized use in digital systems such as medical imaging, computer vision, defense, communication etc. Comparison between two images that look indistinguishable is a formidable task. Two images taken from different sources might look identical but due to different digitizing properties they are not. Whereas small variation in image information such as cropping, rotation, and slight photometric alteration are unsuitable for based matching techniques. In this paper we introduce different matching algorithms designed to facilitate, for art centers, identifying real painting images from fake ones. Different vision algorithms for local image features are implemented using MATLAB. In this framework a Table Comparison Computer Tool “TCCT" is designed to facilitate our research. The TCCT is a Graphical Unit Interface (GUI) tool used to identify images by its shapes and objects. Parameter of vision system is fully accessible to user through this graphical unit interface. And then for matching, it applies different description technique that can identify exact figures of objects.

Keywords: Harris Extraction and SIFT Matching

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Authors: Yin Runmin, Song Changfeng

Abstract:

Image-based Rendering(IBR) techniques recently reached in broad fields which leads to a critical challenge to build up IBR-Driven visualization platform where meets requirement of high performance, large bounds of distributed visualization resource aggregation and concentration, multiple operators deploying and CSCW design employing. This paper presents an unique IBR-based visualization dataflow model refer to specific characters of IBR techniques and then discusses prominent feature of IBR-Driven distributed collaborative visualization (DCV) system before finally proposing an novel prototype. The prototype provides a well-defined three level modules especially work as Central Visualization Server, Local Proxy Server and Visualization Aid Environment, by which data and control for collaboration move through them followed the previous dataflow model. With aid of this triple hierarchy architecture of that, IBR oriented application construction turns to be easy. The employed augmented collaboration strategy not only achieve convenient multiple users synchronous control and stable processing management, but also is extendable and scalable.

Keywords: Image-Based Rendering, Distributed CollaborativeVisualization, Computer Supported Cooperative Work, Model andSimulation, Modular Visualization Environment.

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. To approach this problem, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi

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Ground Penetrating Radar (GPR) is one of the most effective electromagnetic techniques for non-destructive non-invasive subsurface features investigation. Water leak from pipelines is the most common undesirable reason of potable water losses. Rapid detection of such losses is going to enhance the use of the Water Distribution Networks (WDN) and decrease threatens associated with water mains leaks. In this study, GPR approach was developed to detect leaks by implementing an appropriate imaging analyzing strategy based on image refinement, reflection polarity and reflection amplitude that would ease the process of interpreting the collected raw radargram image.

Keywords: Water Networks, Leakage, Water pipelines, Ground Penetrating Radar.

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Authors: L. Strauta, S. Muižniece-Brasava

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Even though legumes possess high nutritional value and have a rather high protein content for plant origin products, they are underutilized mostly due to their lengthy cooking time. To increase the presence of legume-based products in human diet, new extruded products were made of cow peas (Vigna unguiculata (L.) Walp.). But as it is known, adding different moisture content to flour before extrusion can change the physical properties of the extruded product. Experiments were carried out to estimate the optimal moisture content for cow pea extrusion. After extrusion, the pH level had dropped from 6.7 to 6.5 and the lowest hardness rate was observed in the samples with additional 9 g 100g^-1 of moisture - 28±4N, but the volume mass of the samples with additional 9 g100g^-1 of water was 263±3 g L^-1; all samples were approximately 7±1mm long.

Keywords: Cow pea, extrusion-cooking, moisture, size.

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