In this paper, an evolutionary genetic algorithm is used to generate face sketch from the face description. Face sketch generation without face image is extremely important for the law enforcement agencies. The genetic algorithm is used for generating face sketch through several iterations of the algorithm. The face image description is captured through graphical user interface just by clicking options for each face features. Face features are used to extract face images and generate initial population for the genetic algorithm. Genetic operators such as selection, crossover and mutation are used for next generation of the population. The Genetic algorithm cycle is repeated until the user is satisfied with face sketch generated. The novelty of the paper includes face sketch generation from face image description. The result shows that evolutionary based technique for sketch generation produces the desired face sketch.

In this paper the age group estimation is presented based on combination of texture and fractal dimension features. The age of the human is used as one of the important key parameter for computer vision applications. The fractal dimension of the face image and the texture analysis is used to classify the age of the person into the three different groups such as child(10-20), young(21-50) and old(51 and above. The proposed approach of combing the fractal and texture features shows an effective estimation of the age group. The facial age groups are estimated with 90% average accuracy.

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facial feature detection and extraction plays a significant role in face recognition. In this paper, we proposed a new approach for face feature description using support vector machine classifier. Searching image from the image contents is a major challenge in computer vision and pattern recognition. The textual label is assigned to the face feature according to the semantic meaning of the feature. The concept of the textual image description gives advantages to the user to search the image with the help of the visual attributes of the image. The face features like eyes ,nose , mouth are labeled with the visual attributes like small, normal and large.

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