Yahya Sirin

Skeleton Filling Rate for Shape Recognition

As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based shape retrieval algorithm, which starts by drawing circles of increasing radius around skeleton points. Since each skeleton corresponds to the center of a maximally inscribed circle, this process results in circles that are partially inside the shape. Computing the ratio between pixels that lie within the shape and the total number of pixels allows us to distinguish shapes with similar skeletons. Experimental evaluation of the proposed approach including a comparison with the previous techniques demonstrates both effectiveness and robustness of our algorithm for shape retrieval experiments.

2D and 3D shape retrieval using skeleton filling rate

As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based algorithm for 2D and 3D shape retrieval. The algorithm starts by drawing circles (spheres for 3D) of increasing radius around skeletons. Since each skeleton corresponds to the center of a maximally inscribed circle (sphere), this process results in circles (spheres) that are partially inside the shape. Computing the ratio between pixels that lie within the shape and the total number of pixels allows us to distinguish shapes with similar skeletons. Experimental evaluation of the proposed approach including a comprehensive comparison with the previous techniques demonstrates both effectiveness and robustness of our algorithm for shape retrieval using several 2D and 3D datasets.

Dimension reduction selection for increasing naturalness in speech synthesis

Speech synthesis systems are systems that provide great convenience to people on user-computer interaction. These systems can read written text as well as they can process human speech artificially. In this study instead of a monotone robotic speech synthesis, the idea is that it is better suited to human nature to have different types of texts sound differently in their own categories. For this process which is more suitable for human nature, the raw texts are first classified by passing through the text preprocessing step, The audio files are obtained by determining which audio texts are to be sounded with this tone as a result of this classification. Text speech that is not appropriate for its category is provided by differentiating its tonalities. Thus, misclassified documents can be clearly distinguished from tonal differences in audio files.

Distance measure functions with enhanced skeletal points for 2D and 3D

The more digital image production increase, the more effectiveness and productivity of image recognition mechanism and comparison techniques become important. In this study, comparative experiments are made for distribution distance measurement function that is explained in the scope by using skeleton presentation which is obtained from 2D and 3D images of objects. Separate experiments are made in the same conditions for each distance measurement function and at the end of this process suitability of distance measurements for different conditions are discussed by evaluating each result. This study are compared with previous distance measurement methods and experimental evaluations are presented to show effectiveness and powerlessness of the study.

3D shape recognition: Enhanced skeletal points

Digital video production is increasing day after day and the effectiveness and efficiency of the image recognition mechanism has became increasingly important. In this study, a new skeleton-based shape recognition algorithm, which is generated by drawing spheres with increasing radii around the skeleton, is presented. After this operation, drawn spheres partially remain the inside of shapes because each frame corresponds to the center of a maximum tangent sphere. The ratio between number of pixels of the drawn sphere that is remaining in the shape, and the total number of pixels of the drawn sphere is used to identify skeleton similarities and shapes. The experimental evaluation of a comparison with previous techniques and an approach that suggested to show the effectiveness and reliability of the operation is presented.

Efficient shape recognition with skeleton filling rate

As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based shape retrieval algorithm, which starts by drawing circles of increasing radius around skeleton points. Since each skeleton corresponds to the center of a maximally inscribed circle, this process results in circles that are partially inside the shape. Computing the ratio between pixels that lie within the shape and the total number of pixels allows us to distinguish shapes with similar skeletons. Experimental evaluation of the proposed approach including a comparison with the previous techniques demonstrates both effectiveness and robustness of our algorithm for shape retrieval experiments.