erdinc kocer | Selcuk University (Selçuk Üniversitesi) (original) (raw)
Address: Konya, Konya, Turkey
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Within the fast development of knowledge and informatics, there are many new applications and ren... more Within the fast development of knowledge and informatics, there are many new applications and renovations in education field. The Distance Learning is one example of these renovations and applications. In this work, the development duration and application results of a distance learning application intended for master education were explained. This application consists of 4 courses for master education on Computer Education. These are Fuzzy Logic, Artificial Neural Networks, Expert Systems and Soft Computing Methods. The number of students and the successful rate of this application are shown as graphically in the last section.
The reduction of fluid that acts as shock absorber placed in lumbar intervertebral discs causes p... more The reduction of fluid that acts as shock absorber placed in lumbar intervertebral discs causes pains and this case is named as degenerative disc disease. Magentic Resonance Imaging is generally used for diagnosis of this disease by radiologists or doctors. However, due to personal errors such as fatigue, inexperience, oversight, wrong diagnosis is possible. In order to prevent these, computer-aided diagnostic (CAD) methods are mostly preferred. In this work, the performance of two different feature extraction methods is compared. The saggital MR images taken from 9 patients were feature extracted by using grey level co-occurrence matrix (GLCM) and average absolute deviation (AAD) methods. The obtained feature vectors were classified by using multi-layered perceptron (MLP) artificial neural networks.
E xtracting minutiae from fingerprint images is one of the most important steps in automatic fing... more E xtracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. Minutiae are local discontinuities in the fingerprint pattern, mainly terminations and bifurcations. Most of the minutiae detection methods are based on image binarization while some others extract the minutiae directly from gray-scale images. In this work we compare these two approaches and propose two different methods for fingerprint ridge image enhancement. The first one is carried out using local histogram equalization, Wiener filtering, and image binarization. The second method uses a unique anisotropic filter for direct gray-scale enhancement. The results achieved are compared with those obtained through some other methods. Both methods show some improvement in the minutiae detection process in terms of time required and efficiency.
International Journal of Pattern Recognition and Artificial Intelligence, 2008
Procedia Computer Science, 2011
In recent years, the necessity of personal working in traffic control is increasing because the n... more In recent years, the necessity of personal working in traffic control is increasing because the numbers of vehicles in traffic is increasing. To deal with this problem, computer based automatic control systems are being developed. One of these systems is automatic vehicle license plate recognition system. In this work, the automatic vehicle license plate recognition system based on artificial neural networks is presented. In this system, 259 vehicle pictures were used. These vehicle pictures were taken from the CCD camera and then the license plate region dimensioned by 220x50 pixels is determined from this picture by using image processing algorithms. The characters including letters and numbers placing in the license plate were located and determined by using Canny edge detection operator and the blob coloring method. The blob coloring method was applied to the ROI for separation of the characters. In the last phase of this work, the character features were extracted by using average absolute deviation formula. The digitized characters were then classified by using feed forward back propagated multi layered perceptron neural networks. The correct classification rates were given in last section.
Within the fast development of knowledge and informatics, there are many new applications and ren... more Within the fast development of knowledge and informatics, there are many new applications and renovations in education field. The Distance Learning is one example of these renovations and applications. In this work, the development duration and application results of a distance learning application intended for master education were explained. This application consists of 4 courses for master education on Computer Education. These are Fuzzy Logic, Artificial Neural Networks, Expert Systems and Soft Computing Methods. The number of students and the successful rate of this application are shown as graphically in the last section.
The reduction of fluid that acts as shock absorber placed in lumbar intervertebral discs causes p... more The reduction of fluid that acts as shock absorber placed in lumbar intervertebral discs causes pains and this case is named as degenerative disc disease. Magentic Resonance Imaging is generally used for diagnosis of this disease by radiologists or doctors. However, due to personal errors such as fatigue, inexperience, oversight, wrong diagnosis is possible. In order to prevent these, computer-aided diagnostic (CAD) methods are mostly preferred. In this work, the performance of two different feature extraction methods is compared. The saggital MR images taken from 9 patients were feature extracted by using grey level co-occurrence matrix (GLCM) and average absolute deviation (AAD) methods. The obtained feature vectors were classified by using multi-layered perceptron (MLP) artificial neural networks.
E xtracting minutiae from fingerprint images is one of the most important steps in automatic fing... more E xtracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. Minutiae are local discontinuities in the fingerprint pattern, mainly terminations and bifurcations. Most of the minutiae detection methods are based on image binarization while some others extract the minutiae directly from gray-scale images. In this work we compare these two approaches and propose two different methods for fingerprint ridge image enhancement. The first one is carried out using local histogram equalization, Wiener filtering, and image binarization. The second method uses a unique anisotropic filter for direct gray-scale enhancement. The results achieved are compared with those obtained through some other methods. Both methods show some improvement in the minutiae detection process in terms of time required and efficiency.
International Journal of Pattern Recognition and Artificial Intelligence, 2008
Procedia Computer Science, 2011
In recent years, the necessity of personal working in traffic control is increasing because the n... more In recent years, the necessity of personal working in traffic control is increasing because the numbers of vehicles in traffic is increasing. To deal with this problem, computer based automatic control systems are being developed. One of these systems is automatic vehicle license plate recognition system. In this work, the automatic vehicle license plate recognition system based on artificial neural networks is presented. In this system, 259 vehicle pictures were used. These vehicle pictures were taken from the CCD camera and then the license plate region dimensioned by 220x50 pixels is determined from this picture by using image processing algorithms. The characters including letters and numbers placing in the license plate were located and determined by using Canny edge detection operator and the blob coloring method. The blob coloring method was applied to the ROI for separation of the characters. In the last phase of this work, the character features were extracted by using average absolute deviation formula. The digitized characters were then classified by using feed forward back propagated multi layered perceptron neural networks. The correct classification rates were given in last section.