The thesis illustrates the development of DSP-based ¡§Relativity Gene Algorithm For Multiple Faces Recognition System＂. The recognition system is divided into three systems: Ellipsoid location system of multiple human faces, Feature points and feature vectors extraction system, Recognition system algorithm of multiple human faces. Ellipsoid location system of multiple human faces is using CCD camera or digital camera to capture image data which will be recognized in any background, and transmitting the image data to SRAM on DSP through the PPI interface on DSP. Then, using relatively genetic algorithm with the face color of skin and ellipsoid information locate face ellipses which are any location and size in complex background. Feature points and feature vectors extraction system finds facial feature points in located human face by many image process skills. Recognition system algorithm of multiple human faces is using decision by majority. Using characteristic vectors compares every vector in the database. Then, we draw out the highest ID. The recognizable result is over. The experimental result of the developed recognition system demonstrates satisfied and efficiency.

No segmento criminal, uma ferramenta digital capaz de comparar informações sobre suspeitos criminais, restringindo a lista de potenciais criminosos, representa um grande avanço tecnológico. O desafio é conseguir recuperar imagens similares em banco de dados a partir do retrato falado de um suspeito, sendo assim possível localizar as imagens de criminosos no banco de faces da polícia. A importância desse desafio deve-se ao fato que na maioria dos casos, o retrato falado gerado, a partir da descrição verbal de testemunhas é o ponto de partida para o desfecho de muitas investigações. Em vista disto, este trabalho tem por objetivo apresentar um sistema computacional capaz de buscar imagens de faces humanas de um banco de faces através dos esboços das imagens de face, a partir de um retrato falado. Foram feitos retratos falados para comparar com os esboços das imagens das faces humanas presentes em banco de dados e foram recuperadas as mais semelhantes. Na metodologia proposta, as imagens de face passam por um processamento chamado Misturograma, que resulta no esboço da imagem de face, que é utilizado para se comparar com os retratos falados obtidos. O algoritmo proposto usa distância Euclidiana para comparação de semelhança e wavelets de Haar como descritor das imagens. Foram utilizadas as métricas estatísticas de avaliação de desempenho: Recall X Precision e Cumulative Match Score. A metodologia proposta obteve uma precisão de 95% de acertos nas buscas realizadas em Cross Validation, dessa forma mostra-se um método viável para recuperação de imagens a partir de retratos falados. / In the criminal segment, a digital tool able to compare information on criminal suspects, restricting the list of potential criminals, represents a major technological breakthrough. The challenge is to retrieve similar images in the database and thus from the sketch of a suspect you can find images of criminals in the police faces database. The importance of this challenge is due to the fact that in most cases, the sketch generated from the verbal description of witnesses is the starting point for the outcome of many investigations. In view of this, this paper aims to develop a computer system able to search for images of human faces from a database of faces using face images of outlines from a sketch. Sketches were made to compare with the outlines of the images of human faces present in the database and the most similar were retrieved. In the proposed methodology, the face images go through a process called Misturograma, resulting in the outlines of the face image, which is used to compare the obtained sketches. The proposed algorithm uses Euclidean distance to compare the similarity and Haar wavelets as a descriptor of the images. We used the statistical metrics for performance evaluation: Recall X Precision and Cumulative Match Score. The proposed method achieved an accuracy of 95% in carried out searches in Cross Validation thus proves to be a viable method for recovering images from sketches.

No segmento criminal, uma ferramenta digital capaz de comparar informações sobre suspeitos criminais, restringindo a lista de potenciais criminosos, representa um grande avanço tecnológico. O desafio é conseguir recuperar imagens similares em banco de dados a partir do retrato falado de um suspeito, sendo assim possível localizar as imagens de criminosos no banco de faces da polícia. A importância desse desafio deve-se ao fato que na maioria dos casos, o retrato falado gerado, a partir da descrição verbal de testemunhas é o ponto de partida para o desfecho de muitas investigações. Em vista disto, este trabalho tem por objetivo apresentar um sistema computacional capaz de buscar imagens de faces humanas de um banco de faces através dos esboços das imagens de face, a partir de um retrato falado. Foram feitos retratos falados para comparar com os esboços das imagens das faces humanas presentes em banco de dados e foram recuperadas as mais semelhantes. Na metodologia proposta, as imagens de face passam por um processamento chamado Misturograma, que resulta no esboço da imagem de face, que é utilizado para se comparar com os retratos falados obtidos. O algoritmo proposto usa distância Euclidiana para comparação de semelhança e wavelets de Haar como descritor das imagens. Foram utilizadas as métricas estatísticas de avaliação de desempenho: Recall X Precision e Cumulative Match Score. A metodologia proposta obteve uma precisão de 95% de acertos nas buscas realizadas em Cross Validation, dessa forma mostra-se um método viável para recuperação de imagens a partir de retratos falados. / In the criminal segment, a digital tool able to compare information on criminal suspects, restricting the list of potential criminals, represents a major technological breakthrough. The challenge is to retrieve similar images in the database and thus from the sketch of a suspect you can find images of criminals in the police faces database. The importance of this challenge is due to the fact that in most cases, the sketch generated from the verbal description of witnesses is the starting point for the outcome of many investigations. In view of this, this paper aims to develop a computer system able to search for images of human faces from a database of faces using face images of outlines from a sketch. Sketches were made to compare with the outlines of the images of human faces present in the database and the most similar were retrieved. In the proposed methodology, the face images go through a process called Misturograma, resulting in the outlines of the face image, which is used to compare the obtained sketches. The proposed algorithm uses Euclidean distance to compare the similarity and Haar wavelets as a descriptor of the images. We used the statistical metrics for performance evaluation: Recall X Precision and Cumulative Match Score. The proposed method achieved an accuracy of 95% in carried out searches in Cross Validation thus proves to be a viable method for recovering images from sketches.

Facial Ageing (FA) is a very fundamental issue, as ageing in general, is part of our daily life process. FA is used in security, finding missing children and other applications. It is also a form of Facial Recognition (FR) that helps identifying suspects. FA affects several parts of the human face under the influence of different biological and environmental factors. One of the major facial feature changes that occur as a result of ageing is the appearance and development of wrinkles. Facial wrinkles are skin folds; their shapes and numbers differ from one person to another, therefore, an advantage can be taken over these characteristics if a system is implemented to extract the facial wrinkles in a form of maps. This thesis is presenting a new technique for three-dimensional facial wrinkle pattern information that can also be utilised for biometric applications, which will back up the system for further increase of security. The procedural approaches adopted for investigating this new technique are the extraction of two-dimensional wrinkle maps of frontal human faces for digital images and the design of three-dimensional wrinkle pattern formation system that utilises the generated wrinkle maps. The first approach is carried out using image processing tools so that for any given individual, two wrinkle maps are produced; the first map is in a binary form that shows the positions of the wrinkles on the face while the other map is a coloured version that indicates the different intensities of the wrinkles. The second approach of the 3D system development involves the alignment of the binary wrinkle maps on the corresponding 3D face models, followed by the projection of 3D curves in order to acquire 3D representations of the wrinkles. With the aid of the coloured wrinkle maps as well as some ageing parameters, simulations and predictions for the 3D wrinkles are performed.

Facial Ageing (FA) is a very fundamental issue, as ageing in general, is part of our daily life process. FA is used in security, finding missing children and other applications. It is also a form of Facial Recognition (FR) that helps identifying suspects. FA affects several parts of the human face under the influence of different biological and environmental factors. One of the major facial feature changes that occur as a result of ageing is the appearance and development of wrinkles. Facial wrinkles are skin folds; their shapes and numbers differ from one person to another, therefore, an advantage can be taken over these characteristics if a system is implemented to extract the facial wrinkles in a form of maps. This thesis is presenting a new technique for three-dimensional facial wrinkle pattern information that can also be utilised for biometric applications, which will back up the system for further increase of security. The procedural approaches adopted for investigating this new technique are the extraction of two-dimensional wrinkle maps of frontal human faces for digital images and the design of three-dimensional wrinkle pattern formation system that utilises the generated wrinkle maps. The first approach is carried out using image processing tools so that for any given individual, two wrinkle maps are produced; the first map is in a binary form that shows the positions of the wrinkles on the face while the other map is a coloured version that indicates the different intensities of the wrinkles. The second approach of the 3D system development involves the alignment of the binary wrinkle maps on the corresponding 3D face models, followed by the projection of 3D curves in order to acquire 3D representations of the wrinkles. With the aid of the coloured wrinkle maps as well as some ageing parameters, simulations and predictions for the 3D wrinkles are performed.

As the amount of computer mediated information (e.g., emails, documents, multi-media) we need to process grows, our need to rapidly sort, organize and store electronic information likewise increases. In order to store information effectively, we must find ways to sort through it and organize it in a manner that facilitates efficient retrieval. The instantaneous and emergent nature of communications across networks like Twitter makes them suitable for discussing events (e.g., natural disasters) that are amorphous and prone to rapid changes. It can be difficult for an individual human to filter through and organize the large amounts of information that can pass through these types of social networks when events are unfolding rapidly. A common feature of social networks is the images (e.g., human faces, inanimate objects) that are often used by those who send messages across these networks. Humans have a particularly strong ability to recognize and differentiate between human Faces. This effect may also extend to recalling information associated with each human Face. This study investigated the difference between human Face images, non-human Face images and alphanumeric labels as retrieval cues under different levels of Task Load. Participants were required to recall key pieces of event information as they emerged from a Twitter-style message feed during a simulated natural disaster. A counter-balanced within-subjects design was used for this experiment. Participants were exposed to low, medium and high Task Load while responding to five different types of recall cues: (1) Nickname, (2) Non-Face, (3) Non-Face & Nickname, (4) Face and (5) Face & Nickname. The task required participants to organize information regarding emergencies (e.g., car accidents) from a Twitter-style message feed. The messages reported various events such as fires occurring around a fictional city. Each message was associated with a different recall cue type, depending on the experimental condition. Following the task, participants were asked to recall the information associated with one of the cues they worked with during the task. Results indicate that under medium and high Task Load, both Non-Face and Face retrieval cues increased recall performance over Nickname alone with Non-Faces resulting in the highest mean recall scores. When comparing medium to high Task Load: Face & Nickname and Non-Face significantly outperformed the Face condition. The performance in Non-Face & Nickname was significantly better than Face & Nickname. No significant difference was found between Non-Faces and Non-Faces & Nickname. Subjective Task Load scores indicate that participants experienced lower mental workload when using Non-Face cues than using Nickname or Face cues. Generally, these results indicate that under medium and high Task Load levels, images outperformed alphanumeric nicknames, Non-Face images outperformed Face images, and combining alphanumeric nicknames with images may have offered a significant performance advantage only when the image is that of a Face. Both theoretical and practical design implications are provided from these findings.