• Journal of the Institute of Convergence Signal Processing
• /
• v.10 no.1
• /
• pp.7-12
• /
• 2009

In this paper, we propose a directional feature extraction method for off-line handwritten numerals by using the morphological operations. Direction features are obtained from four directional line images, each of which contains horizontal, vertical, right-diagonal and left-diagonal lines in entire numeral lines. Conventional method for extracting directional features uses Kirsch masks which generate edge-shaped double line images for each direction, whereas our method uses directional erosion operations and generate single line images for each direction. To apply these directional erosion operations to the numeral image, preprocessing steps such as thinning and dilation are required, but resultant directional lines are more similar to numeral lines themselves. Our four [$4{\times}4$] directional features of a numeral are obtained from four directional line images through a zoning method. For obtaining the higher recognition rates of the handwrittern numerals, we use the multiple feature which is comprised of our proposed feature and the conventional features of a kirsch directional feature and a concavity feature. For recognition test with given features, we use a multi-layer perceptron neural network classifier which is trained with the back propagation algorithm. Through the experiments with the CENPARMI numeral database of Concordia University, we have achieved a recognition rate of 98.35%.

• Journal of Biosystems Engineering
• /
• v.24 no.5
• /
• pp.431-438
• /
• 1999

The environmental control based on interactive thermoregulatory behavior for swine production has many advantages over the conventional temperature-based control methods. Therefore, this study was conducted to compare various feature selection methods using postural images of growing pigs under various environmental conditions. A color CCD camera was used to capture the behavioral images which were then modified to binary images. The binary images were processed by thresholding, edge detection, and thinning techniques to separate the pigs from their background. Following feature were used for the input patterns to the neural network ; \circled1 perimeter, \circled2 area, \circled3 Fourier coefficients (5$\times$5), \circled4 combination of (\circled1 ＋ \circled2), \circled5 combination of (\circled1 ＋ \circled3), \circled6 combination of (\circled2 ＋ \circled3), and \circled7 combination of (\circled1 ＋ \circled2 ＋ \circled3). Using the above each input pattern, the neural network could classify training images with the success rates of 96%, 96%, 96%, 100%, 100%, 96%, 100%, and testing images with those of 88%, 86%, 93%, 96%, 91%, 90%, 98%, respectively. Thus, the combination of perimeter, area and Fourier coefficients of the thinning images as neural network features gave the best performance (98%) in the behavioral classification.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.12
• /
• pp.7302-7308
• /
• 2014

Detecting target objects robustly in natural environments is a difficult problem in the computer vision and image processing areas. This paper suggests a method of robustly detecting target objects in the environments where reflection exists. The suggested algorithm first captures scenes with a stereo camera and extracts the line and corner features representing the target objects. This method then eliminates the reflected features among the extracted ones using a homographic transform. Subsequently, the method robustly detects the target objects by clustering only real features. The experimental results showed that the suggested algorithm effectively detects the target objects in reflection environments rather than existing algorithms.

• Convergence Security Journal
• /
• v.14 no.7
• /
• pp.23-28
• /
• 2014

This study proposes the design and implementation of the system for a facial expression recognition system. LDP(Local Directional Pattern) feature computes the edge response in a different direction from a pixel with the relationship of neighbor pixels. It is necessary to be estimated that LDP code can represent facial features correctly under various conditions. In this respect, we build the system of facial expression recognition to test LDP performance quickly and the proposed evaluation system consists of six components. we experiment the recognition rate with local micro patterns (LDP, Gabor, LBP) in the proposed evaluation system.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1816-1819
• /
• 2003

As a result of milling operation, we expect to have burr at the outward edge of workpiece. Also, it causes undesirable problems such as deburring cost, low quality of machined surface, and bottleneck in manufacturing process. Though it is impossible to totally remove burr in machining, it is necessary to plan a machining process that minimizes the occurrence of burr. In this paper, a scheme is proposed which identifies the tool path of the milling operation with minimum burr. In the previous research, a Burr Expert System was developed where the feature identification, the cutting condition identification, and the analysis on exit burr formation are the key steps in the program. The Burr Expert System predicts which portion of workpiece would have the exit burr in advance so that we can calculate the burr length of each milling operation. Here, the critical angle determines whether the burr analyzed is an exit burr or not. So the burr minimization scheme becomes to minimize the burr with critical angle. By iterating all the possible tool paths in certain milling operation, we can identify the tool path with minimum burr.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.1
• /
• pp.60-65
• /
• 2010

This paper describes the results of 2D mapping, feature detection and matching to create the surrounding environment in the mounted stereo camera on Mobile robot. Extract method of image's feature in real-time processing for quick operation uses the edge detection and Sum of Absolute Difference(SAD), stereo matching technique can be obtained through the correlation coefficient. To estimate the location of a mobile robot using ZigBee beacon and encoders mounted on the robot is estimated by Kalman filter. In addition, the merged gyro scope to measure compass is possible to generate map during mobile robot is moving. The Simultaneous Localization and Mapping (SLAM) of mobile robot technology with an intelligent robot can be applied efficiently in human life would be based.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.874-877
• /
• 2012

This paper proposes the new method based on contour following method with directional angle to segment the cell into the nuclei. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. The nuclei were successfully diagnosed as normal and abnormal. this paper, improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the Thyroid Gland cell image with difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a result of experiment using features proposed in this paper, get a better segmentation rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells. The methods described in this paper be used immediately for discrimination of neoplastic cells.

• Proceedings of the Korean Information Science Society Conference
• /
• 1998.10c
• /
• pp.384-386
• /
• 1998

The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction(HCI). Many methods hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMMs is proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin-color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and thus, produces a trajectory. The spotting a feature database, the proposed approach use the mesh feature code for codebook of HMM. In our experiments, 1300 alphabetical and 1300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfying recognition rate for the images with different sizes, shapes and skew angles.

• Korean Journal of Cognitive Science
• /
• v.8 no.4
• /
• pp.55-62
• /
• 1997

We proposed a method for locating of mouth using deformable templates, described by a parameterized template. An energy function is defined which links, edges, peaks, valleys in image intensity to corresponding properties of the template. The template deforms itself by altering its parameter values to minimize the energy function. The minimized energy function's parameter values can be used as descriptors for the feature. We propose a method for locating mouth fast, accurately by limiting a range of parameters' value and getting initial value of parameters' by preprocessing.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.541-545
• /
• 1997

This paper presents a modified geometric active contour model or edge detection and segmentation of computed tomography(CT) scan images. The method is based on the level setup approach developed by Osher and Sethian and the modeling of propagation fronts with curvature dependent speeds by Malladi. Based on above algorithms, the geometric active contour is obtained through a particular level set of hypersurface lowing along its gradient force and curvature force. This technique retains the attractive feature which is topological and geometric flexibility of the contour in recovering objects with complex shapes and unknown topologies. But there are limitations in this algorithm which are being not able to separate the object with weak difference from neighbor object. So we use speed limitation filter to overcome those problems. We apply a 2D model to various synthetic cases and the three cases of real CT scan images in order to segment objects with complicated shapes and topologies. From the results, the presented model confirms that it attracts very naturally and efficiently to the desired feature of CT scan images.